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2mo ago

Sr Databricks Data Engineer

Deloitte Morristown, NJ

Morristown, NJ

2mo ago Closed

$116k - $229k/yr Full time Big Data Data Architecture Data Engineer

This position is no longer accepting applications (closed Aug 18, 2026).

Job Description

Join Deloitte in Morristown, NJ, onsite, for a Senior Databricks Data Engineer role that combines technical leadership with opportunities to shape enterprise data platforms. The position offers a competitive salary range of USD 116,200 to 229,100 per year and a discretionary annual incentive program. You will design, build, and optimize cloud-based data engineering solutions on Databricks to modernize data platforms, enable analytics and AI, and drive data-driven decision making across the enterprise.

Responsibilities

Champion Best Practices: Establish, document, and promote best-in-class approaches for data architecture, integration, and modelling.
Pipeline Ownership: Oversee the design, development, and maintenance of robust data pipelines and data architectures that support large-scale, enterprise data needs.
Drive Excellence: Initiate and manage efforts to improve data quality, operational efficiency, and process scalability.
Team and Technology Lead: Evaluate, pilot, and integrate new big data and analytics technologies, ensuring the organization remains at the cutting edge. Lead, coach, and develop teams of data engineers and architects, fostering technical growth and effective project delivery.
Data Governance: Consult on, design, and implement governance, security, and compliance strategies tailored to modern cloud data ecosystems.
Communication: Communicate technical concepts and business value to diverse stakeholders, including executives, business leads, and technology teams.
DevOps and Automation: Oversee the implementation of CI/CD practices with tools such as Azure DevOps, AWS Code Pipeline, Jenkins, TFS, or PowerShell for streamlined deployments and operations.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field
5+ years of hands-on experience in data engineering with a focus on Databricks on Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms
Experience with data warehousing, third normal form (3NF), dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark
1+ year leading complex, cross-functional data projects and technical teams, including experience with Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and performance optimization of data engineering pipelines, code, and compute resources
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Technologies

Databricks, AWS, Azure, Google Cloud Platform (GCP)
Delta Lake, Apache Spark, PySpark
Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows
Apache Airflow, Unity Catalog, Databricks Lakeflow
Azure DevOps, AWS Code Pipeline, Jenkins, TFS, PowerShell

Benefits

Discretionary annual incentive program

Preferred

Master's degree in Computer Science, Engineering, or a related field
Experience in one or more of AWS, Azure, and GCP cloud ecosystems and associated big data services
Experience tuning and optimizing performance in Databricks and Apache Spark environments
Experience with Databricks Lakeflow
Experience with artificial intelligence and machine learning solutions

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2mo ago

Senior Data Engineer

Software Resources, Inc. Lake Buena Vista, FL

Lake Buena Vista, FL

2mo ago Closed

Contract Senior Analytics Apache Beam

This position is no longer accepting applications (closed Aug 18, 2026).

Job Description

This contract Senior Data Engineer opportunity is based in Lake Buena Vista, FL, with a hybrid work arrangement. The role centers on designing, building, and implementing data engineering systems and ETL/ELT pipelines, with on-site presence required Monday through Thursday and remote work available on Fridays.

Responsibilities

Collaborate with stakeholders to gather and refine data requirements.
Define source-to-target data mappings to support integration efforts.
Develop and review data validation scripts to ensure data quality.
Design, implement, and monitor ETL and ELT data pipelines.
Produce datasets used as inputs for analytical models and visualizations.
Participate in technical reviews to ensure high quality deliverables.
Develop an understanding of business domains and processes to inform assigned work.
Communicate data engineering progress to project leadership.
Actively contribute to meetings and discussions with the project team.

Requirements

Bachelor's degree in Computer Science, Mathematics, Software Engineering, or a related field, or equivalent experience.
Minimum of 2 years of experience in ELT/ETL development.
5+ years of experience building ELT/ETL pipelines using SQL and Python.
2+ years developing and maintaining data pipelines with a framework such as Apache Flink, Apache Beam, or Kafka Streams.
Experience and understanding of one or more business domains to assist in gathering and refining data requirements and data design solutions.
Experience developing in multiple environments (Dev, QA, Prod) and implementing DevOps procedures for code deployment and promotion.
Strong database design knowledge and proficiency with platforms such as PostgreSQL or Snowflake.
Experience managing and deploying code using GitLab or GitHub.
Ability to articulate solutions and communicate complex technical concepts to non-technical team members.

Technologies

Snowflake
SQL
Python
Apache Flink
Apache Beam
Kafka Streams
Docker
Kubernetes
AWS
Databricks
PostgreSQL
GitLab
GitHub

Benefits

Medical, dental, and vision coverage
401(k) with company match
Short-term disability
Life insurance with AD&D

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2mo ago

AWS Cloud Data Engineer

System One McLean, VA 🇺🇸 Remote

McLean, VA

2mo ago Closed

Contract Amazon Emr Amazon Rds Amazon Web Services

This position is no longer accepting applications (closed Aug 18, 2026).

Job Description

System One is seeking an AWS Cloud Data Engineer for a remote, long-term contract in McLean, VA. This role centers on designing, building, and maintaining scalable data pipelines in AWS, with emphasis on ETL/ELT, data modeling, governance, and data quality. The position requires the ability to obtain a Federal Public Trust clearance.

Responsibilities

Design, build, and sustain scalable data pipelines and processing solutions within AWS environments.
Collaborate with AWS Cloud DBAs and cross-functional teams to migrate data from legacy applications to AWS, ensuring performance, reliability, and security.
Develop ETL and ELT workflows to ingest, transform, and load data into data lakes, data warehouses, and analytical platforms.
Leverage AWS data services such as S3, Glue, Step Functions, Lambda, Kinesis, EMR, Athena, Redshift, RDS, and Aurora.
Create and maintain data models, schemas, documentation, and data access patterns for both transactional and analytical workloads.
Implement data quality checks, monitoring, governance controls, and compliance practices for data retention, privacy, and security requirements.

Requirements

Ability to obtain a Federal Public Trust clearance.
Bachelor's degree in Computer Science, Data Engineering, or a related field; four additional years of relevant experience may substitute for a degree.
Minimum of 6 years of data engineering experience, including at least 3 years working in AWS cloud environments.
Strong experience with AWS data services including S3, Glue, DMS, Athena, Redshift, EMR, Kinesis, and Lambda.
Proficiency in Python, Scala, or Java for data processing and pipeline development.
Experience with SQL and relational databases such as PostgreSQL or Oracle, and NoSQL databases such as DynamoDB or DocumentDB.
Understanding of data modeling concepts for transactional and analytical workloads.
Experience with Infrastructure as Code tools such as Terraform, CloudFormation, or CDK, and CI/CD pipelines for data engineering workflows.
Strong analytical, problem-solving, collaboration, and communication skills with a focus on data quality and system reliability.

Technologies

S3
Glue
Step Functions
Lambda
Kinesis
EMR
Athena
Redshift
RDS
Aurora
Python
Scala
Java
SQL
PostgreSQL
Oracle
DynamoDB
DocumentDB
Terraform
CloudFormation
CDK
Apache Spark
Apache Airflow
Git
Docker
Kubernetes
ECS
EKS
QuickSight
Tableau
Power BI
JSON
Avro
Parquet
ORC

Benefits

Medical insurance
Dental insurance
Vision insurance
Spending accounts
Life insurance
Voluntary plans
401(k) plan

NICE TO HAVE

AWS Certified Data Engineer – Associate certification
AWS Certified Solutions Architect or other relevant AWS certifications
Experience with Apache Spark, Apache Airflow, or AWS-native orchestration tools
Knowledge of data formats such as JSON, Avro, Parquet, and ORC, including compression techniques
Familiarity with Git and collaborative development practices
Knowledge of container technologies including Docker, Kubernetes, ECS, or EKS
Experience with data visualization tools such as QuickSight, Tableau, or Power BI
Understanding of data privacy regulations and compliance frameworks
Experience tuning and optimizing distributed data processing systems
Knowledge of networking, security, and IAM policies related to data engineering workflows

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2mo ago

BI & Analytics Analyst/Data Engineer

JSSA Rockville, MD

Rockville, MD

2mo ago Closed

Full time Analyst Analytics Azure Data Lake

This position is no longer accepting applications (closed Aug 18, 2026).

Job Description

JSSA seeks a Hybrid BI and Analytics Analyst/Data Engineer in Rockville, MD, to bridge data engineering with analytics across the organization. The role spans end-to-end analytics from SQL Server data warehouse design to empowering self-service Power BI reporting, working closely with IT partners and operational leaders to transform raw data into reliable, actionable insights.

Responsibilities

Collaborate with IT business partners and operational leaders to design analyses that uncover opportunities to improve care, evaluate adherence to clinical best practices, and measure outcomes.
Contribute to ensuring data repositories deliver consistent, reusable data by partnering with staff to develop, implement, and guide standards and best practices.
Promote best-practice knowledge to business stakeholders to enable self-service analytics rather than IT-owned development.
Own self-service reporting datasets, including DAX measures, data models, and row-level security.
Translate business requirements into clear analytical deliverables, manage stakeholder expectations, and iterate based on feedback.
Monitor report usage and data quality, proactively identifying and resolving issues.
Document data definitions, metric logic, and report lineage to support data literacy across the agency.
Utilize technical tools to query, manipulate, and summarize data from multiple sources.
Assist in designing, developing, maintaining, and updating databases to meet departmental and organizational needs.
Design and build star schema data warehouse objects in SQL Server, including fact and dimension tables and aggregate layers.
Write and maintain T-SQL stored procedures, ETL pipelines, and staging-to-warehouse data loads.
Develop and own source-to-target mapping documentation for new data domains.
Integrate data from source systems.
Contribute to data quality, pipeline reliability, and warehouse performance optimization.
Support the adoption of self-service analytics by building clean, well-documented datasets.
Document current data architecture, define logical and physical data, and establish an agency data blueprint.
Manage and support the data warehouse solution (Wherescape RED), SQL Server, and related technologies.
Define operational monitoring and alerting tools to ensure end-to-end delivery of trusted, quality data from source systems to consumption.
Establish best-practice standards and processes for data automation, orchestration, and transformation.
Identify, design, implement and manage a master data management solution for client and employee subjects, working with stakeholders to define data quality standards and operational DQ processes.

Requirements

Bachelor’s degree required; Master’s degree highly preferred.
5–7+ years of experience in a BI, analytics, or data engineering role.
Strong proficiency in SQL Server and T-SQL, including stored procedures, window functions, and query optimization.
Hands-on experience building and maintaining Power BI reports and semantic models (DAX, Power Query).
Hands-on experience with Wherescape OLAP solutions; familiarity with Azure Analysis Services, Azure Data Lake, and Azure Synapse Analytics as alternative OLAP options.
Experience integrating or working with EHR data (reports, APIs, or data exports).
Familiarity with star schema and dimensional modeling concepts (Kimball methodology a plus).
Python experience for data wrangling, automation, or pipeline scripting.
Experience with Microsoft Master Data Services (MDS), including defining entities and business rules.
Experience with Microsoft Data Quality Services (DQS) and SQL Server Integration Services (SSIS).
Comfort across the full analytics stack from raw source data to end-user reports.
Strong communication skills able to explain data concepts to non-technical stakeholders.
Advanced proficiency with Microsoft Office tools (Power BI) and SQL, plus experience with EMR systems (hospice, homecare, and/or mental health) is desirable.

Technologies

SQL Server
T-SQL
Power BI
DAX
Power Query
Wherescape RED
Azure Analysis Services
Azure Data Lake
Azure Synapse Analytics
Microsoft Master Data Services (MDS)
Microsoft Data Quality Services (DQS)
SQL Server Integration Services (SSIS)

Benefits

Competitive salary
Benefits package
Healthy work-life balance
Collaborative team environment
Opportunities for personal growth and professional development

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2mo ago

Data & Analytics Engineer

Electro-Mechanical Corporation Bristol, VA

Bristol, VA

2mo ago Closed

$85k - $110k/yr Full time Analytics Azure Data Factory Azure Platform

This position is no longer accepting applications (closed Aug 18, 2026).

Job Description

Data & Analytics Engineer responsible for designing, building, and maintaining a scalable enterprise data platform using Microsoft Fabric, Power Platform, and leading visualization tools (Power BI and Tableau), based in Bristol, VA.

Responsibilities

Build and sustain a scalable enterprise data platform using Microsoft Fabric components, including OneLake, Data Factory, Data Engineering, Data Warehouse, Real-Time Analytics, and Lakehouse architecture.
Create and operate data ingestion, transformation, and orchestration pipelines from diverse internal and external sources.
Design data models to support enterprise reporting, analytics, AI, and operational decision-making.
Develop reusable data products and semantic models to ensure consistency and scalability across the organization.
Architect and deploy ETL and ELT workflows using Microsoft Fabric and related Azure technologies.
Integrate ERP, CRM, operational systems, cloud applications, APIs, and third-party data sources.
Maintain data quality, reliability, and performance through monitoring, validation, and optimization.
Establish data governance, metadata management, lineage, and security controls.
Develop enterprise dashboards, scorecards, and analytics solutions using Power BI and Tableau.
Build scalable semantic models and datasets that enable self-service analytics.
Improve visualization performance and user experience.
Set reporting standards, KPIs, and data definitions across business functions.
Partner with stakeholders to translate requirements into actionable analytics solutions.
Define best practices for data management, access controls, privacy, and compliance.
Define and maintain enterprise data standards and governance frameworks.
Enforce role-based security and data access policies within Microsoft Fabric and reporting platforms.
Support audit, compliance, and regulatory requirements.
Assess emerging technologies and best practices in cloud analytics, data engineering, and AI.
Promote adoption of modern data architecture principles and analytics capabilities.
Mentor team members and advance data literacy across the organization.
Contribute to roadmap planning and strategic data initiatives.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, Statistics, or a related field; equivalent combination of education and relevant experience may be considered.
3-5 years of experience in data engineering, analytics engineering, business intelligence, or related roles.
Experience designing, developing, and supporting data pipelines and analytical solutions in a production environment.
Strong SQL skills with the ability to develop complex queries, views, stored procedures, and data transformations.
Experience building and maintaining ETL/ELT pipelines.
Experience with modern cloud data platforms such as Fabric, Snowflake, Databricks, or Azure Synapse.
Knowledge of data warehousing concepts, dimensional modeling, and data architecture best practices.
Experience with enterprise integrations, middleware, APIs, and data migration methodologies.
Experience with Microsoft Azure, AWS, or Google Cloud Platform.
Understanding of data quality frameworks, monitoring, and validation processes.
Experience implementing data governance, metadata management, and master data practices.
Knowledge of security, privacy, and compliance considerations related to enterprise data.
Experience supporting Finance, Supply Chain, Manufacturing, or Commercial analytics.
Experience in manufacturing, distribution, industrial, private equity-backed, or multi-site organizations.

Technologies

Microsoft Fabric, OneLake, Data Factory, Data Warehouse
Power BI, Tableau, Power Apps, Power Automate, Dataverse
Git, SQL, Snowflake, Databricks, Azure Synapse
Microsoft Azure, AWS, Google Cloud Platform
Python, Spark, PySpark
Azure DevOps, Power Platform, API development

Preferred Skills

Microsoft Azure Data Services
Python, Spark, or PySpark
Azure DevOps
DataOps and MLOps concepts
Real-time analytics and streaming architectures
AI/ML integration within Microsoft Fabric
Enterprise ERP and CRM integrations

Preferred Certifications

Microsoft Certified: Fabric Analytics Engineer Associate
Microsoft Certified: Power BI Data Analyst Associate
Microsoft Certified: Azure Data Engineer Associate

Compensation

Salary: USD 85,000 - 110,000 per year

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2mo ago

Data Scientist III, Rapid & Rural Logistics (R2L) Science & AI

Amazon.com Services LLC New York, NY

New York, NY

2mo ago Closed

$159k - $237k/yr Full time Amazon Quicksight Analytics Business Analytics

This position is no longer accepting applications (closed Aug 18, 2026).

Job Description

Based onsite in New York, NY, this Data Scientist III role supports Amazon's Rapid & Rural Logistics (R2L) Science & AI with data-driven insights, ML models, and causal inference to inform the team charter and enable cross-functional impact.

Responsibilities

Shape and refine the team's data science charter.
Explore data assets and identify opportunities to delight customers through data-driven insights and machine learning models.
Provide rapid analytics support to multiple stakeholders across business and technical domains.
Proactively identify high-potential opportunities using data-driven insights and apply various machine learning techniques and causal inference methods to develop solutions.
Dive deeply into data and deliver timely analyses with clear findings and actionable recommendations.
Balance uncertainty with delivering customer-focused results when opportunities may be uncertain.

Requirements

5+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab, etc.).
4+ years of hands-on data science experience.
Experience with statistical models, including multinomial logistic regression.

Technologies

SQL
Python
R
SAS
Matlab
AWS QuickSight
Tableau
R Shiny

Benefits

Medical, dental, and vision coverage
Maternity and parental leave options
Paid time off
401(k) plan with company matching
Health insurance (medical, dental, vision, prescription)
Basic Life and AD&D insurance
Supplemental life plans
Employee Assistance Program (EAP)
Mental health support
Medical Advice Line
Flexible Spending Accounts
Adoption and surrogacy reimbursement coverage

Preferred Qualifications

2+ years of data visualization experience using AWS QuickSight, Tableau, R Shiny, or similar tools
Experience managing data pipelines
Experience as a leader and mentor on a data science team

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2mo ago

Sr Data Scientist, GenAI Economics and Analytics

Amazon.com Services LLC Seattle, WA

Seattle, WA

2mo ago Closed

$159k - $215k/yr Full time Amazon Quicksight Analytics Artificial Intelligence

This position is no longer accepting applications (closed Aug 18, 2026).

Job Description

Senior data scientist focusing on GenAI economics and analytics for Alexa shopping experiences, onsite in Seattle, WA, partnering with senior leaders to drive analytics strategy and inform executive decision-making.

Salary: USD 159,200 - 215,300 per year

Responsibilities

Develop customer and shopping-mission cohorts to analyze behavior with and without Alexa across the end-to-end shopping journey.
Determine which query shapes and interaction patterns deliver the most value for specific cohorts and shopping missions.
Build predictive models to forecast customer re-engagement and long-term adoption of Rufus based on interaction quality and downstream shopping outcomes.
Create, operationalize, and publish scalable metrics and dashboards that surface actionable insights for data-driven product growth and executive decision-making.
Collaborate with Product, Engineering, and Economics teams to translate analytical insights into roadmap priorities and customer-focused improvements.

Requirements

5+ years of experience with data querying languages (eg, SQL), scripting languages (eg, Python), or statistical/mathematical software (eg, R, SAS, Matlab, etc.).
4+ years of data scientist experience.
Experience with statistical models such as multinomial logistic regression.

Technologies

SQL
Python
R
SAS
Matlab
AWS QuickSight
Tableau
R Shiny

Benefits

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave

About the Team

The Alexa for shopping Analytics team focuses on understanding how GenAI powered shopping tools transform customer behavior across the shopping lifecycle—from inspiration and problem solving, to product research, selection, purchase, and post-purchase support. We build foundational measurement frameworks that enable teams to evaluate performance, identify what AI experiences resonate most with customers, and uncover opportunities for improvement. Our work informs product direction and customer-facing improvements.

Preferred Qualifications

2+ years of data visualization experience using AWS QuickSight, Tableau, R Shiny, etc.
Experience managing data pipelines
Experience as a leader and mentor on a data science team