Informatica

Informatica Data Jobs

31 jobs found

Today

Senior Data Engineer

Brooksource New York, NY 🇺🇸 Remote

New York, NY

Today

$65 - $85/hr Full time Senior Analytics API

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Job Description

The Senior Data Engineer will design, develop, and maintain scalable data pipelines and architectures that support advanced analytics and business intelligence, leveraging big data ecosystems, cloud platforms, and robust data modeling.

Responsibilities

Design, build, and optimize large-scale ETL pipelines using Informatica, Talend, Apache Spark, and Apache Hive.
Create and sustain data architectures on cloud environments including AWS, Azure Data Lake, and other public clouds.
Partner with cross-functional teams to capture requirements and translate them into scalable data solutions.
Develop and implement data models employing dimensional modeling techniques for data warehousing and analytics.
Oversee data integration from linked data, RESTful APIs, and additional external sources.
Ensure data quality, security, and compliance throughout the data lifecycle.
Support machine learning model deployment through efficient data pipeline integration.
Apply SQL, Python, Java, Bash, and shell scripting to automate processes and improve efficiency.
Contribute to Agile practices by participating in sprint planning, reviews, and continuous improvement efforts.
Document data workflows and architecture diagrams to promote transparency and knowledge sharing.

Requirements

Proven experience as a Data Engineer or similar role focusing on big data systems and cloud-based architectures.
Extensive knowledge of AWS services (S3, Redshift, Glue), Azure Data Lake, Hadoop components, and other public cloud offerings.
Strong proficiency with SQL databases including Microsoft SQL Server, Oracle, and cloud-based options.
Hands-on ETL/ELT development experience using Informatica or Talend.
Demonstrated expertise in data modeling techniques, including dimensional modeling for enterprise data warehouses.
Proficiency in programming languages such as Python and Java, with automation scripting in VBA, Bash, and shell scripting.
Familiarity with business intelligence tools like Looker or similar platforms for reporting and analysis.
Understanding of RESTful API integration for linked data access.
Knowledge of analytics approaches related to database design, query management, model training, and analytics methodologies.
Experience delivering value in fast-paced environments using Agile methodologies.

Technologies

Informatica
Talend
Apache Spark
Apache Hive
AWS
Azure Data Lake
Hadoop
S3
Redshift
Glue
Microsoft SQL Server
Oracle
SQL
Python
Java
VBA
Bash scripting
Shell Scripting
Looker
RESTful API

Pay

$65.00 - $85.00 per hour

Location

New York, NY (remote)

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Today

Lead Data Engineer / Data Architect

Glint Tech Solutions LLC Charlotte, NC

Charlotte, NC

Today

Full time Azure Data Factory Azure Data Lake Storage Azure Synapse Analytics

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Job Description

Glint Tech Solutions LLC is steering an enterprise modernization program for a major US retail eCommerce platform, where a robust data architecture underpins fast, reliable customer experiences. The Lead Data Engineer / Data Architect will shape the enterprise data strategy and design scalable platforms through re-architecture, database migrations, and cloud-native microservices migration. This onsite role is based in Charlotte, NC.

Responsibilities

Design and own enterprise data architecture supporting high-volume retail eCommerce operations
Build and maintain ETL/ELT pipelines using Azure Data Factory, Synapse Analytics, and Databricks/pySpark
Design conceptual, logical, and physical data models for efficient data storage and retrieval
Implement data warehousing solutions including dimensional modeling, star schemas, Data Mesh, Delta Lakehouse, and Data Vault
Lead database migrations and microservices migrations to unified cloud-native solutions
Integrate data from databases, APIs, and external providers via API integration and message queuing
Embed metadata and governance processes into cloud-based data platforms
Lead and mentor cross-functional engineering teams while driving technical strategy and stakeholder communications

Requirements

8+ years of overall experience with at least 1 year in an architect-level role
3+ years of hands-on Azure Data Factory and Azure Synapse Analytics experience
Deep Microsoft Azure expertise including Data Lake Storage, Databricks, pySpark, Cosmos DB, and PostgreSQL
Strong SQL proficiency for complex queries, transformations, and cloud performance tuning
Experience with Azure MI, Cosmos DB, Analysis Services, and Informix
Proficiency in Python and Python-based ETL tools
Shell scripting experience (Bash, Unix, or Windows)
Proven ability to lead teams, define technical strategy, and communicate across organizational levels

Technologies

Azure Data Factory
Azure Synapse Analytics
Databricks
pySpark
Data Lake Storage
Cosmos DB
PostgreSQL
SQL
Python
Bash
Unix
Windows
Azure MI
Analysis Services
Informix
Elasticsearch
Docker
Kubernetes
Delta Lake
Delta Lakehouse
Data Mesh
Data Vault

Company overview

Glint Tech Solutions is a women-owned global staffing and IT recruiting firm connecting top technical talent with leading enterprise clients across the United States and Canada.

Nice-to-have skills

Elasticsearch experience
Docker and Kubernetes familiarity
Performance tuning and pipeline optimization expertise
Azure, Databricks, or relevant cloud certifications

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1d ago

Staff Engineer II - Senior Data Engineer

Western Alliance Bank Phoenix, AZ

Phoenix, AZ

1d ago

Full time Senior Analytics Azure Data Factory

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Job Description

Responsibilities

Design, develop and deploy data engineering solutions using Azure Data Factory, Azure Synapse Analytics, and Azure DevOps to support regulatory reporting and the bank’s LFI strategy.
Craft data solution designs that can be handed off to engineering teams for execution, prioritizing component reuse to maximize efficiency.
Build ETL and data pipeline capabilities, considering data creation, transformation, storage, archiving, analysis, and sharing across the bank and partner systems.
Implement Azure DevOps CI/CD pipelines for all data solutions in alignment with the bank’s technical standards.
Apply Test Driven Development to all designed, built, and deployed data solutions.
Lead the implementation of outcomes from Data Governance and Enterprise Architecture.
Oversee the migration of multidimensional cubes to tabular models to enhance analytics and performance.
Utilize Power BI to design, deploy, and visualize tabular cubes, enabling effective business intelligence integration and insights.
Perform data exploration and profiling with tools such as Excel and Informatica.
Participate actively in data architecture decision making.
Provide technical mentorship to team members and other data professionals.
Collaborate with product owners and business stakeholders to understand requirements and operational processes.
Incorporate built-in quality and compliance by design in all data solutions.
Review Azure Data Factory pipelines, Synapse artifacts, and other scripts produced by data engineers, delivering feedback to uphold quality standards.

Requirements

Bachelor’s degree in engineering or a related field; a Master’s or MBA is preferred.
7+ years of data engineering experience covering ETL concepts, enterprise data warehousing, database principles, and related tools; proficiency in Azure Data Factory, Azure Synapse Analytics, and/or Databricks is preferred.
2+ years designing, implementing, and supporting cloud data solutions; strong preference for Azure Data Lake, Azure Data Factory, Azure Data Services, Azure Synapse, Azure Logic Apps, and Azure DevOps.
Advanced experience with at least one RDBMS and query languages such as T-SQL, PL/SQL, or Spark SQL.
Advanced expertise in conceptual, logical, and physical data design.
Azure certifications such as Azure Fundamentals, Azure Data Engineer, Azure Data Scientist, and/or Azure DevOps Engineer are preferred.
Familiarity with data science and analytics tools such as SAS, Tableau, and Power BI.
Familiarity with multi-cloud data management and transformation platforms or tools such as Databricks and Snowflake.
Experience with Agile, SAFe, and/or Scrum methodologies is preferred.
Experience integrating with data quality, data catalog, and data lineage tools is preferred.
Previous leadership experience is preferred.
Intermediate to advanced knowledge of general financial services or banking is preferred.
Advanced knowledge of regulatory and legal compliance obligations, rules, and industry standards.
Proven ability to lead cross-functional teams and manage multiple projects concurrently, including pipeline development and Azure DevOps usage across multiple projects.
Strong strategic thinking with the ability to align projects with organizational goals, lead and motivate teams, resolve conflicts, and mitigate risks; governance patterns tied to intake, technical reviews, and architectural compliance are advantageous.
Excellent spoken and written communication skills.
May require up to 25% travel.

Technologies

Azure Data Factory
Azure Synapse Analytics
Azure DevOps
Azure Data Lake
Azure Logic Apps
Power BI
Excel
Informatica
Databricks
Snowflake
SAS
Tableau
Azure Data Services
T-SQL
PL/SQL
Spark SQL

Benefits

Competitive salaries
Ownership stake in the company
Medical and dental insurance
Time off
Strong 401k matching program
Tuition assistance program
Employee volunteer program
Wellness program

Location

Block 23, Phoenix, AZ (onsite)

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2d ago

Data Engineer Staff

Lockheed Martin Corporation Lexington, KY

Lexington, KY

2d ago

Full time Analytics Big Data Business Analytics

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Job Description

Lockheed Martin Corporation is seeking a skilled Data Engineer Staff to join its data engineering team in Lexington, Kentucky, on a hybrid work arrangement. The role centers on delivering end-to-end data solutions across the full data processing pipeline, designing, building, and operating scalable pipelines with an emphasis on security, performance, and DoD/SOFSA compliance.

Responsibilities

Build, test, and maintain robust data pipelines (batch & streaming) that clean, transform, and aggregate raw data into analytic ready data stores.
Implement data quality checks, smart caching, and virtualization techniques to guarantee consistency and reliability.
Build automated data management conduits that support machine learning data flows.
Collaborate with the Data Architect to create conceptual, logical, and physical data models that support business needs.
Define functional capabilities, security, backup, and recovery specifications for each solution.
Design and maintain systems that collect, store, and present data across the enterprise.
Conduct data profiling, requirement analysis, and performance tuning throughout the solution lifecycle.
Deploy, monitor, and optimize ETL/ELT processes (e.g., Informatica, Talend) and related reporting/analytics layers.
Develop and implement data mining and data warehousing programs to enrich the enterprise data ecosystem.
Identify and resolve production incidents; tune system parameters for optimal throughput and latency.
Evaluate, integrate, and validate new releases or platform upgrades.
Manage the compilation, cataloging, caching, distribution, and retrieval of data and maintain test data records.
Define and enforce best practice standards, certification processes, and metadata management policies for data objects.
Participate actively in the Data Governance Working Group.
Implement data management standards, requirements, and specifications and ensure compliance with data classification and handling rules through access control and security best practices.
Assist early stage risk identification and mitigation for task order activities.
Support Critical Design Reviews (CDRs) and advise Integrated Product Teams (IPTs) on data related risks and mitigation strategies.
Serve as the technical liaison to Systems Engineering, IPT engineers, and other disciplines to ensure complete, documented requirements allocation for IT and data systems.
Prepare and release engineering drawings and associated data system documentation.
Advise on and design the integration of new data technology solutions (e.g., IBM Cloud Pak for Data) into the SOFSA enterprise IT environment.
Advise higher level leadership on critical data management issues and emerging technology trends.
Report directly to the Data Architect and provide status updates on pipeline health, performance metrics, and risk registers.
Apply data acquisition, cleaning, transformation, and ingestion best practices for machine learning data conduits.
Assess and address methodological limitations to ensure reliable data delivery.
Read, interpret, write, modify, and execute simple scripts (e.g., PERL, VBS) on Windows and UNIX systems for parsing large files, automating manual tasks, and fetching/processing remote data.
Record, manage, and validate test data.
Establish data security controls, develop data dictionaries, and apply data mining techniques (e.g., file system searches).
Perform data pre processing (imputation, dimensionality reduction, normalization, transformation, extraction, filtering, smoothing).
Conduct transformation analytics (aggregation, enrichment, processing).

Requirements

Bachelor’s degree in Artificial Intelligence, Computer Science, Information Systems, Data Engineering, or a related field (Master’s preferred).
Data‑mining and data‑warehousing principles.
Database management systems, query languages, table relationships, and views.
Proficiency with Hadoop, Java, Python, SQL, Hive, and PIG for data exploration.
DataOps processes and best practices.
Data‑security roles and responsibilities; ability to implement access‑control and encryption safeguards.
Knowledge of how to collect, store, monitor, and validate test data.
Ability to assess methodological limitations and recommend mitigation strategies.

Technologies

Hadoop, Java, Python, SQL, Hive, PIG
Informatica, Talend, IBM Cloud Pak for Data
AWS, Azure, GCP
PERL, VBS
Microsoft Power BI Report Server, Deltek COBRA
Microsoft SharePoint, SAP, Teamcenter
PowerShell, Oracle SQL Server, Microsoft SQL Server

Benefits

Flexible Schedules
Competitive pay
Comprehensive benefits

Security Clearance

This position requires a government security clearance, you must be a US Citizen for consideration.

Clearance Level

Secret

Other Important Information

Expression of Interest: By applying to this job, you are expressing interest in this position and could be considered for other career opportunities where similar skills and requirements have been identified as a match. Should this match be identified you may be contacted for this and future openings.
Ability to Work Remotely: Part-time Remote Telework: The employee selected for this position will work part of their work schedule remotely and part of their work schedule at a designated Lockheed Martin facility. The specific weekly schedule will be discussed during the hiring process.
Work Schedules: Lockheed Martin supports a variety of alternate work schedules that provide additional flexibility to our employees. Schedules range from standard 40 hours over a five day work week while others may be condensed. These condensed schedules provide employees with additional time away from the office and are in addition to our Paid Time off benefits.
Schedule for this Position: Non- standard 40 hour work week as assigned by leader

Experience Level

Experienced Professional

Business Unit

MISSILES AND FIRE CTRL (S0806)

Relocation Available

Possible

Career Area

Data Science

Type

Task Order/IDIQ

Shift

First

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2d ago

Data Engineer AI

Quest Global Sunnyvale, CA

Sunnyvale, CA

2d ago

$105k - $110k/yr Full time Analytics Artificial Intelligence Business Intelligence

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Job Description

Quest Global is hiring onsite in Sunnyvale, CA for a Data Engineer AI role, offering a salary of USD 105,000 - 110,000 per year. This position centers on building robust data pipelines, validating data quality, exploring datasets for trends and insights, and enabling AI integration to support business decisions. The role provides a robust benefits package that starts on day one, along with opportunities to contribute to data driven initiatives and AI enabled solutions.

Responsibilities

Perform root cause analysis on processes and data to identify opportunities for improvement and answer questions
Build processes that support data transformation, workload management, data structures, dependency and metadata
Perform data validation checks, identify and rectify errors, and maintain a quality standard throughout the data lifecycle
Explore datasets to identify trends, patterns, and insights
Conduct analyses for stakeholders and other non technical professionals; build models to generate actionable insights for making efficient business decisions
Build data pipelines that clean, transform, and aggregate data from disparate sources
Work with data to solve business problems, building and maintaining the infrastructure to answer questions and improve processes
Streamline data science workflows, adding value to product offerings and building out the customer lifecycle and retention models

Requirements

Snowflake
SQL
AI integration
Agentic AI
Tableau

Technologies

Snowflake
SQL
Tableau
ThoughtSpot
Python
Excel
Numbers
Quip
Keynote
Miro
Slack
datarobot

Benefits

401(k) matching
Dental insurance
Health insurance
Paid time off
Vision insurance
Employer paid Life Insurance, Short- & Long-Term Disability

Work requirements

You must be able to commute to and from the location with your own transportation arrangements to meet the required working hours
Shop floor environment, which may include extensive walking, and the ability to lift up to 40 lbs

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9d ago

Senior Data Analyst with Informatica

CGI Group, Inc. Reston, VA

Reston, VA

9d ago

$84k - $108k/yr Full time Senior Analyst Analytics

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Job Description

Senior Data Analyst with Informatica supporting enterprise data platforms in a fast paced financial services setting, delivering data analysis, Informatica development, and production support from a Reston, VA client site with a hybrid work model.

Responsibilities

Investigate data variances
Troubleshoot production issues
Analyze source to target mappings
Implement data corrections
Collaborate closely with internal business stakeholders and technical teams
Analyze data issues
Review Informatica workflows and mappings
Develop and validate data corrections
Document business and technical requirements
Support production environments
Conduct stakeholder discussions
Ensure successful implementation of solutions
Identify root causes
Validate solutions
Ensure data integrity across multiple systems
Explain technical findings to non technical users
Make targeted code modifications when needed
Navigate complex data flows
Operate within a modern cloud based ecosystem leveraging AWS S3 and enterprise data integration technologies

Requirements

Minimum 5 years in business analysis, data analysis, or related data management roles
Recent, hands on Informatica development and production support experience
Strong track record of analyzing complex data issues and identifying root causes in production environments
Hands on experience reading, troubleshooting, and modifying Informatica mappings, workflows, and ETL processes
Advanced Oracle SQL skills for data analysis, validation, troubleshooting, and data correction
Solid understanding of data warehousing concepts, data marts, data lineage, and source to target mappings
Experience comparing and validating data across multiple systems using tools such as Toad
Ability to perform data corrections, validate results, and certify data quality after implementation
Strong problem solving and investigative skills with focus on resolving production issues
Experience in Agile environments using Jira and Confluence
Ability to communicate technical findings effectively to business users and internal stakeholders
Experience gathering, documenting, and translating business requirements into technical solutions
Comfortable working independently while managing multiple priorities and deadlines
Familiarity with AWS based data environments, particularly AWS S3, is beneficial
Understanding of application development concepts and ability to interpret existing code implementations
Strong testing and validation skills with end to end quality verification ownership
Excellent written, verbal, and presentation skills
Mortgage industry experience (single family or multifamily) is a plus
Python experience is a nice-to-have

Technologies

Informatica
Oracle SQL
AWS S3
Toad
Jira
Confluence
Python

Benefits

Competitive compensation
Comprehensive insurance options
Matching contributions through the 401(k) plan and the share purchase plan
Paid time off for vacation, holidays, and sick time
Paid parental leave
Learning opportunities and tuition assistance
Wellness and Well-being programs

Other Information

A reasonable estimate of the current range for this role in the United States is USD 83,800 - 108,300 per year.

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9d ago

Senior Data Analyst - Global Payments Network

Capital One Richmond, VA

Richmond, VA

9d ago

$101k - $115k/yr Full time Senior Analyst Analytics

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Job Description

In Capital One’s Global Payments Network within Finance, the Senior Data Analyst will drive data analysis, governance, and the development of data solutions in an Agile setting, spanning Innovation, Business Intelligence, and Data Management responsibilities.

Responsibilities

Conduct data analysis in an Agile environment alongside technology, product, business, and data professionals, frequently delivering reports.
Ensure data capabilities meet regulatory requirements.
Deliver reporting, analysis, and data validations to support presentations, predictive modeling, and ad hoc requests.
Apply analytic and technical skills to design, implement, and maintain well-governed data solutions addressing business problems.
Leverage open source and digital technologies to mine complex and varied data sources and platforms.
Create and maintain data solutions, tools, and capabilities that enable self service for data consumers.
Demonstrate the ability to quickly learn new technologies to advance multiple initiatives.
Collaborate with the business to translate needs into tools, metrics, and dashboards for insights and data visualization.
Lead analyses that yield meaningful insights for business strategy.
Promote adherence to data quality principles, including metadata, lineage, and business definitions.
Work with technology teams to manage security controls and data access governance.
Develop tools to monitor and report on data quality.

Qualifications and Requirements

Candidates must hold or be pursuing a Bachelor’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or related) with at least two years of data analytics experience; or hold or be pursuing a Master’s degree with expected completion by the start date.
At least one year of experience with at least one scripting language.
At least one year of experience using a business intelligence visualization tool.
At least one year of experience querying, analyzing, and working with data languages and platforms.