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Azure Synapse Analytics Jobs in Washington (NOW HIRING)

BakerHostetler

Data Solutions Engineer

Washington, DC

$129K - $155K/yr

Proficiency in the following tools, technologies, and data concepts: • Azure Data Factory, Azure SQL Database, PostgreSQL, Azure Blob Storage, Azure Data Lake Storage • Azure Synapse Analytics ...

eSolutionsFirst, LLC

Data Engineer

Mclean, VA · On-site

$117K - $141K/yr

Hands-on experience with Azure Data Services including Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure SQL Database, and Azure Synapse Analytics. * Strong experience with Databricks ...

TEKsystems

Practice Architect-AI/ML

Hanover, MD · Remote

$136K - $204K/yr

Azure OpenAI, Azure Machine Learning, Cognitive Services, and/or Azure Synapse Analytics • Basic proficiency in Python, R, or other scripting/AI-related languages • Understanding of cloud-native ...

MDAEdge

Medicaid Data Systems Analyst

Washington, DC · On-site

MDAEdge is seeking a Medicaid Data Systems Analyst to support data modernization efforts. The role ... Server and Azure Synapse • 5+ years of hands-on experience with SSIS, SSAS, SSRS, Azure ...

MDAEdge

Senior Data Engineer

Washington, DC · On-site

$119K - $162K/yr

... in Azure Synapse for advanced analytics and AI-readiness. • Implement Row-Level Security (RLS) and automated data masking for PHI/PII per HIPAA, CMS MARS-E, and NIST standards. • Develop ...

Innosoft Corporation

Azure Cloud Architect

Washington, DC · On-site

$180 - $240/hr

Data platform experience across Azure SQL, Cosmos DB, PostgreSQL Flexible Server, Synapse Analytics, Microsoft Fabric, and Data Lake Storage, from both an administration and a solution design ...

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Azure Synapse Analytics information

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$69.1K

$116.7K

$146.1K

How much do azure synapse analytics jobs pay per year?

As of Aug 8, 2026, the average yearly pay for azure synapse analytics in Washington is $116,657.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,100.00 and $138,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Azure Synapse Analytics position, and why are they important?

Success in an Azure Synapse Analytics role requires strong proficiency in data engineering, SQL, data modeling, and analytics, typically supported by a background in computer science or related fields. Familiarity with Azure Synapse Studio, data integration tools, big data platforms, and certifications such as Microsoft Certified: Azure Data Engineer Associate are highly beneficial. Excellent problem-solving, communication, and teamwork skills help professionals effectively collaborate with stakeholders and respond to business needs. These skills and qualities enable professionals to design robust data solutions, optimize analytics workflows, and drive meaningful insights for organizations.

What does Azure Synapse Analytics do?

Azure Synapse Analytics is a cloud-based data integration and analytics service that enables data professionals to ingest, prepare, manage, and analyze large datasets. It combines data warehousing, big data analytics, and data integration tools, allowing users to build end-to-end data solutions using SQL, Spark, and other technologies within a unified environment.

What are the typical daily responsibilities of someone working with Azure Synapse Analytics?

Professionals working with Azure Synapse Analytics typically spend their days designing and implementing data pipelines, integrating diverse data sources, and optimizing big data workflows within the Azure ecosystem. They may also work closely with data scientists, business analysts, and application developers to ensure data accuracy and facilitate advanced analytics or machine learning projects. Regular tasks can include troubleshooting performance issues, managing data security, and automating data processes. Collaboration and effective communication with cross-functional teams are key aspects of the work environment, helping to deliver accurate and actionable insights for decision-making.

What is an Azure Synapse Analytics?

An Azure Synapse Analytics job typically involves designing, implementing, and optimizing data integration, warehousing, and big data solutions using Azure Synapse. Professionals in this role work with data engineers, analysts, and business stakeholders to streamline data pipelines, enhance query performance, and ensure data security. They leverage Synapse SQL, Spark, and data integration tools to manage and analyze large datasets efficiently. Strong knowledge of cloud infrastructure, security best practices, and performance optimization techniques is essential for success in this role.

What are the most commonly searched types of Azure Synapse Analytics jobs in Washington? The most popular types of Azure Synapse Analytics jobs in Washington are:
What are popular job titles related to Azure Synapse Analytics jobs in Washington? For Azure Synapse Analytics jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Azure Synapse Analytics jobs in Washington look for? The top searched job categories for Azure Synapse Analytics jobs in Washington are:
Azure Synapse Analytics jobs near you
Infographic showing various Azure Synapse Analytics job openings in Washington as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 7% Part Time, and 5% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $116,657 per year, or $56.1 per hour.

Data Engineer (Fraud Analytics & Investigative Support)

Praescient Analytics

Fairfax, VA • On-site, Remote

$117K - $140K/yr

Full-time

Retirement, PTO

Re-posted 13 days ago

Job description

Location: Remote (Occasional Travel May Be Required)
Clearance: Ability to obtain and maintain a Public Trust
U.S. Citizenship is Required.
Position Overview:
Praescient Analytics is seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines supporting advanced fraud analytics and investigative solutions for a federal oversight organization. This individual will play a critical role in ensuring diverse data sources are efficiently ingested, transformed, governed, and made available for analytics, machine learning, graph analytics, and investigative support.
The ideal candidate is a hands-on engineer who enjoys solving complex data integration challenges while building modern cloud-native data pipelines that prioritize quality, reliability, scalability, and performance. They understand that high-quality analytics begin with high-quality data and are committed to developing robust data engineering solutions that enable timely, accurate, and defensible analytic products.
Key Responsibilities:
  • Design, develop, maintain, and optimize scalable ETL pipelines supporting advanced analytics and investigative workloads.
  • Ingest, transform, and integrate structured and unstructured data from diverse sources including flat files, JSON, XML, Excel, APIs, graph databases, relational databases, and other evolving data formats.
  • Develop and optimize data pipelines supporting both streaming and batch ingestion frameworks.
  • Manage, organize, and optimize data within modern cloud-based analytics platforms, including Databricks Unity Catalog, SQL Server managed instances, and Lakehouse architectures.
  • Develop efficient SQL and Python-based data transformation processes that support downstream analytics, machine learning, graph analytics, and business intelligence solutions.
  • Implement data quality validation, lineage tracking, metadata management, and monitoring processes to ensure data reliability and integrity throughout the analytics lifecycle.
  • Collaborate with Data Scientists, Graph Data Scientists, Investigative Analysts, Forensic Accountants, and Project Managers to understand data requirements and support analytic initiatives.
  • Troubleshoot pipeline failures, optimize performance, and continuously improve scalability, reliability, and maintainability of enterprise data solutions.
  • Support enterprise data governance by implementing data management standards, documenting data assets, and ensuring compliance with enterprise data management (EDM) policies.
  • Contribute to data architecture improvements, ingestion strategies, and modernization efforts that enhance overall analytic capabilities.

Required Qualifications:
  • Must have experience with Fraud Analysis
  • Three (3) or more years of professional experience in data engineering or a related technical field.
  • Demonstrated experience designing, building, maintaining, and optimizing scalable ETL pipelines across diverse data sources.
  • Strong SQL and Python programming skills, or equivalent technologies, for data ingestion, transformation, and processing.
  • Experience ingesting and transforming data from flat files, JSON, XML, Excel, APIs, graph databases, relational databases, and other structured and unstructured data sources.
  • Experience loading, managing, and optimizing data within Databricks Unity Catalog, SQL Server managed instances, or comparable cloud-based data platforms.
  • Experience working with streaming and batch ingestion frameworks and modern Lakehouse architectures.
  • Demonstrated ability to implement data quality controls, lineage tracking, reliability monitoring, and performance optimization processes.
  • Familiarity with enterprise data governance, enterprise data management (EDM), metadata management, and data quality best practices.
  • Strong analytical, problem-solving, written, and verbal communication skills.

Preferred Qualifications:
Preference will be given to candidates with demonstrated experience in one or more of the following areas:
  • Supporting fraud detection, anomaly detection, financial oversight, program integrity, or investigative analytics environments.
  • Building cloud-native data engineering solutions utilizing Azure Databricks, Azure Data Lake Storage (ADLS), Microsoft SQL Server, Microsoft Fabric, Azure Synapse Analytics, Power BI, Neo4j, Git repositories, or comparable cloud data platforms.
  • Developing scalable data pipelines supporting machine learning, artificial intelligence (AI), graph analytics, natural language processing (NLP), or advanced analytics solutions.
  • Working with public, non-public, commercial, financial, law enforcement, or cross-agency datasets supporting fraud detection and investigative missions.
  • Designing and implementing Lakehouse architectures, Delta Lake, data partitioning strategies, and performance optimization techniques for large-scale analytics environments.
  • Developing automated data quality validation, metadata management, lineage tracking, schema evolution, and monitoring capabilities.
  • Supporting enterprise data governance initiatives, data catalogs, master data management, and compliance with organizational data standards.
  • Utilizing orchestration and workflow tools such as Apache Spark, Databricks Workflows, Azure Data Factory, Airflow, or comparable pipeline automation technologies.
  • Collaborating within Agile software development teams using Git-based version control, sprint planning, backlog management, and continuous integration/continuous deployment (CI/CD) practices.
  • Supporting Offices of Inspector General (OIGs), federal oversight organizations, law enforcement agencies, or other government data modernization initiatives.

What We're Looking For:
We're looking for a data engineer who is passionate about building reliable, scalable data foundations that power advanced analytics. The ideal candidate enjoys working with complex data ecosystems, solving integration challenges, and continuously improving the quality, performance, and accessibility of enterprise data. They understand that trustworthy analytics depend on trustworthy data and take pride in developing robust engineering solutions that enable investigators and analysts to uncover fraud, waste, abuse, and emerging risks with confidence.
What you can expect from us:
  • Real opportunity for career growth in an environment where your achievements will be celebrated
  • Constant collaboration with numerous teams to ensure client success
  • A team that respects and embraces your ideas and expertise
  • Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
  • A workplace dedicated to supporting and bettering public safety and government agencies

Benefits:
  • Competitive salary based on qualifications and experience
  • Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
  • 401(k) with company match
  • Travel & performance incentives
  • 3 weeks paid time off (plus Federal Holidays)
  • $5K annual training allowance
  • $500 book allowance
  • Tuition reimbursement program

Praescient Analytics is an Equal Employment Opportunity employer. Employment decisions are based on merit, qualifications, experience, performance, business needs, and applicable contract requirements. Praescient does not unlawfully discriminate or provide disparate treatment based on race, ethnicity, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable law.
Praescient Analytics acknowledges the applicable clause and provision updates implementing Executive Order 14398, Addressing DEI Discrimination by Federal Contractors, and the related FAR/RFO updates, including FAR 52.222-90 where applicable. Praescient does not engage in racially discriminatory DEI activities, including disparate treatment based on race or ethnicity in recruitment, hiring, promotion, contracting, program participation, training, mentoring, leadership development, or allocation of company resources. Praescient's employment and contracting decisions are made based on merit, qualifications, experience, performance, business needs, and applicable contract requirements.
Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information.
US Citizenship Required
Interested Candidates: Please forward your resume to recruiting@praescientanalytics.com and please visit our website to apply online at www.praescientanalytics.applicantstack.com/x/openings.

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