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13d ago

IT Specialist (Data Engineer)

US Commodity Futures Trading Commission Washington, DC

Washington, DC

13d ago

$152k - $224k/yr Full time Data Engineer Data Governance Data Integration

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Job Description

The IT Specialist (Data Engineer) role sits in the Division of Data (DoD), within the Data Operations and Standards Branch (DOSB) of the U.S. Commodity Futures Trading Commission. The position focuses on developing, implementing, and operating data strategies to support enterprise analytics and data governance across the agency.

Responsibilities

Architect, deploy, and sustain enterprise data environments including data lakes, data warehouses, and lakehouse architectures.
Design and evolve data models such as normalized, dimensional, star, and snowflake schemas to enable advanced analytics.
Build ETL and ELT pipelines for structured and semi-structured data with automated data quality monitoring.
Develop and manage event-driven and streaming data pipelines using contemporary orchestration frameworks.
Implement data governance, classification, retention, and stewardship practices aligned to federal standards.
Apply Zero Trust security principles and support Authority to Operate processes consistent with NIST SP 800-53, FISMA, and FedRAMP.

Requirements

U.S. Citizenship
Background or security investigation
May be required to serve a one-year probationary period
Selective Service Registration is required for males born after December 31, 1959
Attention to detail
Customer service orientation
Information management skills
Problem solving abilities
CT-13: Designing and implementing enterprise data architecture, pipelines, and modeling solutions
CT-13: Applying federal data governance and security frameworks
CT-13: Developing data integration and orchestration solutions
CT-13: Supporting BI, analytics, and machine learning workflows
CT-13: Applying DevOps practices to data engineering

THIS JOB IS OPEN TO

The public: U.S. Citizens, Nationals or those who owe allegiance to the United States
Clarification from the agency: Applications will be accepted from all U.S. Citizens

Location

Washington, DC, onsite

Compensation

Salary range: USD 152,377 - 223,819 per year

Experience

Minimum experience required: 1 year

Agency Contact Information

Contact: Jenna Giles
Phone: 202-839-0603
Fax: 202-501-0018
Email: jgiles@cftc.gov
Address: Commodity Futures Trading Commission, Three Lafayette Centre, 1155 21st St NW, Washington, DC 20581, United States

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13d ago

Senior Data Engineer

Liberty Mutual Boston, MA

Boston, MA

13d ago

$114k - $197k/yr Full time Senior Analytics Data Analytics

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Job Description

Liberty Mutual Investments Technology is seeking a Senior Data Engineer to design, build, and support enterprise data pipelines and data management solutions for market, reference, and financial data on the EDM platform (formerly Markit EDM). The role sits in a hybrid Boston-based environment and offers a salary range of USD 114,000 to 197,000 per year, reflecting the combined responsibilities of hands-on development and cross-functional collaboration.

Responsibilities

Design, build, maintain, and support data management workflows, data models, and integration pipelines.
Configure and sustain ingestion, validation, enrichment, matching, and distribution processes within the EDM system.
Enable reporting, analytics, and downstream data integrations connected to the EDM platform.
Create and maintain scalable ETL/ELT pipelines for market, reference, and transactional data.
Ingest data from internal and external vendors, APIs, flat files, and enterprise applications.
Implement data quality checks, reconciliations, exception handling, and monitoring processes.
Collaborate closely with data engineers, analysts, and product stakeholders in an agile, squad-based model.
Mentor junior engineers, participate in code reviews, and promote engineering best practices and standards.

Requirements

Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience.
Five or more years of data engineering experience building and maintaining scalable data platforms and pipelines.
Strong SQL skills with expertise in data modeling and data warehousing concepts.
Hands-on experience delivering solutions within Markit EDM.
Experience working with market data, reference data, or financial services data platforms.
Proficiency in Python for data processing, automation, and integration tasks.
Experience diagnosing and resolving complex production data issues.
Excellent communication and stakeholder management abilities.

Technologies

SQL
Python
Markit EDM
Microsoft SQL Server

Benefits

Comprehensive benefits package
Workplace flexibility
Professional development opportunities
Opportunities provided through our Employee Resource Groups

Description

This role has a required hybrid Boston work arrangement.

Fair Chance Notices

California
Los Angeles Incorporated
Los Angeles Unincorporated
Philadelphia
San Francisco

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13d ago

Senior Data Engineer - Vice President

Citi Irving, TX

Irving, TX

13d ago

$126k - $189k/yr Full time Senior Big Data Bigdata

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Job Description

Join Citi in Irving, TX for an on-site Senior Data Engineer - Vice President role that centers on collaborative, client-focused data solutions. The position offers a comprehensive benefits package including medical, dental, and vision coverage; a 401(k); life, accident, and disability insurance; wellness programs; paid time off, sick leave, and holidays. The role is full-time with a salary range of USD 125,760 to 188,640 per year. Requires a bachelor’s degree and a minimum of 6 years of hands-on data engineering experience, with leadership responsibilities in an enterprise setting.

Benefits

Medical, dental, and vision coverage
401(k)
Life, accident, and disability insurance
Wellness programs
Planned time off (vacation)
Unplanned time off (sick leave)
Paid holidays

Responsibilities

Architect and sustain scalable ETL/ELT pipelines using PySpark, Spark SQL, and Delta Lake on Databricks to efficiently ingest, transform, and integrate large-scale datasets across cloud environments.
Cloud Data Platform Management: design, implement, and manage data solutions on cloud platforms (AWS, GCP, Azure) leveraging cloud-native services for storage, processing, and analytics.
Big Data Technologies: work with Databricks, Snowflake, and open table formats such as Apache Iceberg to process petabyte-scale datasets.
Optimize Spark workloads and Databricks clusters by tuning jobs, partitioning strategies, caching, and autoscaling to boost performance and manage costs.
Implement and govern Lakehouse architecture with Delta Lake, enforcing data quality, schema evolution, and governance via Unity Catalog for reliable analytics and downstream use.
Lead the design and architecture of Starburst-based data solutions to ensure enterprise-level scalability, performance, and reliability.
Execute data federation strategies using Starburst connectors to unify access across data lakes, RDBMS, NoSQL, and cloud storage.
Performance Optimization: identify bottlenecks in pipelines and queries, improving storage and processing efficiency.
Develop and optimize robust data pipelines with a strong emphasis on data governance, ensuring quality, lineage, and compliant data flow from ingestion to consumption.
Data Modeling and Architecture: design data models that support BI, analytics, and ML use cases, building a robust, secure, scalable data architecture.
AI and Machine Learning Collaboration: partner with data scientists to support AI model development and deployment, contributing to RAG and Agentic AI initiatives through data infrastructure support.
Agile Methodology: operate effectively in an Agile environment, participating in sprint planning, daily stand-ups, and retrospectives to deliver milestones.
Leadership and Project Guidance: provide technical leadership, mentor junior engineers, and influence architectural decisions aligned with client needs and strategic goals.
Stakeholder and Client Interaction: act as a primary point of contact for stakeholders and clients, communicating progress and translating business requirements into actionable technical tasks.

Requirements

Python: expert-level proficiency with Python and its data ecosystem (Pandas, NumPy, Dask); experience delivering production-grade data processing, automation, and API development.
PySpark: extensive hands-on experience with the Spark framework, deep knowledge of the DataFrame API, Spark SQL, and performance tuning for distributed processing.
Databricks: proven work on the Databricks Lakehouse Platform, including Delta Lake, structured streaming, and optimizing Spark jobs within the environment.
Ab Initio: strong practical experience with the Ab Initio suite (GDE, Co>Operating System, Conduct>It) for enterprise-grade ETL workflows.
Snowflake: hands-on experience designing and maintaining Snowflake data warehouses, including modeling, RBAC, performance tuning, Snowpipe, and Time Travel.
Starburst/Trino: experience with federated query engines to provide unified access across diverse data sources and data systems.
Apache Iceberg: familiarity with open table formats for managing large analytic datasets.
Cloud provider experience: multi-year, in-depth experience with at least one major cloud provider (AWS, GCP, or Azure).
Cloud-native data pipelines: practical experience building pipelines with cloud-native services such as AWS Glue, Lambda, S3, Redshift; Azure Data Factory, Synapse; or Google Cloud Composer, Dataflow, and BigQuery.
Data lifecycle for ML: solid understanding of the data lifecycle required for machine learning projects.
AI data pipelines: experience building data pipelines to support AI/ML models, with interest or exposure to preparing data for advanced AI applications such as vector databases for RAG and Agentic AI.
Agile Proficiency: strong familiarity with Agile and Scrum methodologies and iterative delivery.
Leadership & Influence: demonstrated ability to provide technical leadership and guide architectural decisions aligned with client needs and long-term strategy.
Client Engagement: excellent communication and interpersonal skills, capable of articulating complex concepts to diverse audiences and building stakeholder relationships.
6-10 years of hands-on data engineering experience, preferably in a large-scale enterprise or financial services environment.
Experience leading project work streams and mentoring junior team members.
Relevant industry certifications (e.g., AWS Certified Big Data, Google Professional Data Engineer, Snowflake SnowPro).
Containerization and orchestration: experience with Docker and Kubernetes.
Deep understanding of data governance, data quality, and data security principles.
Strong analytical and problem-solving skills with the ability to work independently or as part of a team.
Experience as Applications Development Manager and senior-level experience in an Applications Development role, with stakeholder and people management experience.
Proven project management skills and a solid grasp of industry practices and standards.
Clear and concise written and verbal communication.

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13d ago

Databricks Data Engineer

Deloitte Tempe, AZ

Tempe, AZ

13d ago

$87k - $171k/yr Full time Analytics Artificial Intelligence Azure Databricks

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Job Description

Join Deloitte in Tempe, AZ, onsite, as a Databricks Data Engineer. This role supports analytics and AI initiatives through the design, construction, and continual optimization of cloud-based data pipelines. The position offers a salary range of USD 86,700 to 170,900 per year and the opportunity to work closely with both client teams and Deloitte experts to deliver large-scale data transformation programs. You will gain hands-on experience with Databricks, Apache Spark, Python, and SQL while contributing to the modernization of enterprise data platforms and influencing how data supports decision making and innovation.

Responsibilities

Create and sustain data pipelines and engineering solutions using Databricks, Apache Spark, Python, and SQL.
Support the modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns.
Design and manage batch and streaming data workflows that underpin reporting, analytics, and AI use cases.
Apply data architecture, integration, and modeling practices to improve data quality, scalability, and platform performance.
Collaborate with client teams and Deloitte colleagues to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics.
3+ years of experience in data engineering, ETL development, or data platform engineering.
2+ years building data pipelines in Databricks using Apache Spark, Python, and SQL.
Experience implementing data models, data integration patterns, and cloud-based data processing workflows.
Experience with at least one cloud platform: AWS, Azure, or Google Cloud Platform.
Ability to travel approximately 50% on average.
Limited immigration sponsorship may be available.

Technologies

Databricks
Apache Spark
Python
SQL
AWS
Azure
GCP
Delta Lake
Databricks Workflows
Unity Catalog
Git

Preferred

Experience with Delta Lake, Databricks Workflows, and Unity Catalog
Experience using Git-based version control and CI/CD pipelines
Experience supporting batch and streaming data workloads
Experience with data warehousing, lakehouse architecture, and performance optimization
Experience supporting analytics or machine learning data pipelines
Experience working in consulting or client service delivery environments

Accommodation

Information for applicants with a need for accommodation: details available here

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13d ago

Databricks Data Engineer

Deloitte Arlington, VA

Arlington, VA

13d ago

$87k - $171k/yr Full time Artificial Intelligence Azure Databricks Big Data

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Job Description

Deloitte's Databricks Data Engineer role is based onsite in Arlington, VA, within the Core AI & Data practice. The position centers on designing, building, and optimizing cloud-based data engineering solutions that leverage Databricks to support large-scale transformations, analytics, and AI initiatives. The salary range is USD 86,700 to 170,900 per year.

Responsibilities

Design, build, and sustain data pipelines and engineering solutions using Databricks, Apache Spark, Python, and SQL.
Support modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns.
Develop and manage batch and streaming data workflows that support reporting, analytics, and AI use cases.
Apply data architecture, integration, and data modeling practices to improve data quality, scalability, and platform performance.
Collaborate with client and Deloitte teams to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs.
Demonstrate the following skills expected for the role:
Ability to work independently and as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to provide clear guidance to others

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics
3+ years of experience in data engineering, ETL development, or data platform engineering
2+ years of experience building data pipelines in Databricks using Apache Spark, Python, and SQL
Experience implementing data models, data integration patterns, and cloud-based data processing workflows
Experience working with at least one cloud platform: AWS, Azure, or GCP
Ability to travel 50% on average depending on client engagements
Limited immigration sponsorship may be available

Technologies

Databricks
Apache Spark
Python
SQL
Delta Lake
Databricks Workflows
Unity Catalog
Git-based version control
CI/CD pipelines
AWS
Azure
GCP

Preferred

Experience with Delta Lake, Databricks Workflows, and Unity Catalog
Experience using Git-based version control and CI/CD pipelines
Experience supporting batch and streaming data workloads
Experience with data warehousing, lakehouse architecture, and performance optimization
Experience supporting analytics or machine learning data pipelines
Experience working in consulting or client service delivery environments

Accommodation Information

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applic...

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13d ago

Data Engineer

Citi Jersey City, NJ

Jersey City, NJ

13d ago

$142k - $213k/yr Full time AWS Aws Glue Big Data

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Job Description

Citi, a global financial services leader, offers an onsite Data Engineer position in Jersey City that sits at the intersection of data platforms and business impact. This AVP level role blends hands-on development with advisory duties as you help define and deploy new or revised application systems in close coordination with the Technology team. A bachelor’s degree or equivalent experience and a minimum of five years in related roles are required, with a salary range of USD 142,320 to 213,480 per year.

Responsibilities

Conduct feasibility studies, time and cost estimates, IT planning, risk assessment, applications development, model development, and establish and implement new or revised applications systems and programs to meet specific business needs or user areas
Monitor and control all phases of the development process from analysis to design, construction, testing, and implementation, and provide user and operational support on applications to business users
Apply in-depth specialty knowledge of applications development to analyze complex problems, evaluate business and system processes, consider industry standards, and make evaluative judgments
Recommend and develop security measures in post-implementation analyses to ensure successful system design and functionality
Consult with users, clients, and other technology groups on issues, propose advanced programming solutions, and install or assist with customer exposure systems
Ensure essential procedures are followed and help define operating standards and processes
Serve as advisor or coach to new or lower level analysts
Operate with limited direct supervision and exercise independence of judgment and autonomy
Act as subject matter expert to senior stakeholders and other team members
Assess risk in business decisions, upholding Citi’s reputation and safeguarding clients and assets by complying with laws and regulations, applying ethical judgment, and escalating and reporting control issues with transparency

Requirements

5-8 years of relevant experience
Experience in systems analysis and programming of software applications
Experience in managing and implementing successful projects
Working knowledge of consulting or project management techniques or methods
Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements

Technologies

AWS Glue
AWS Athena
Airflow
Snowflake
MongoDB
Oracle
PostgreSQL
Unix shell scripting
Python
PySpark
Ab Initio (EME, GDE, Co-op)

Benefits

Discretionary and formulaic incentive and retention awards
Medical, dental & vision coverage
401(k)
Life, accident, and disability insurance
Wellness programs
Paid time off packages (vacation, sick leave, and paid holidays)

Job specifics

Job family group: Technology
Job family: Applications Development
Time type: Full time
Primary location: Jersey City, New Jersey, United States
Primary location full time salary range: $142,320.00 - $213,480.00

Posting timeline

Anticipated posting close date: Jun 09, 2026

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14d ago

Analytics Engineer - AI Trainer

DataAnnotation Pittsburgh, PA 🇺🇸 Remote

Pittsburgh, PA

14d ago

$40 - $60/hr Full time Advanced Analytics Ai Trainer Analyst

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Job Description

Analytics Engineer - AI Trainer at DataAnnotation offers a fully remote role with a Pittsburgh, PA base and a flexible schedule to evaluate AI-generated quantitative work and design problems for training and benchmarking AI systems.

Location and compensation overview

Location: Pittsburgh, PA (remote)

Hourly rate: USD 40 - 60 per hour

Responsibilities

Assess AI-generated quantitative outputs for technical accuracy and practical validity, covering statistical analysis, predictive modeling, scientific reasoning, and data-driven insights.
Develop and solve quantitative tasks used to train and benchmark AI systems, including forecasting, experimental analysis, optimization, and statistical inference.
Produce clear, well-documented technical explanations and analytical code.
Offer actionable feedback that informs the next generation of AI models focused on quantitative reasoning.

Requirements

2+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related fields.
Some coding experience with comfort writing and reviewing analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design (A/B testing, hypothesis testing, regression, classification, time-series forecasting).
Fluency in English with strong writing skills (native or bilingual level).
Bachelor's degree in a quantitative field is preferred; master's or PhD is a plus.
Relevant credentials are beneficial (e.g., Kaggle competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise).

Benefits

Fully remote work arrangement, enabling you to operate from the US, Canada, UK, Ireland, Australia, or New Zealand.
Flexible schedule to choose projects and determine when you work.
Competitive hourly pay, with rates up to $60 per hour and opportunities for higher-paying projects with strong performance.
Impactful work that helps shape AI systems designed for data and analytics reasoning.

Note

Payment is processed via PayPal.
We will never ask for money from you.
This position is available to applicants located in the US, Canada, UK, Ireland, Australia, and New Zealand.