Designs, builds, and maintains secure, scalable data solutions across Azure Databricks and Azure Synapse Analytics.
Local candidates only will be considered for this position.
This role supports data integration, pipeline development, data modeling, governance, and documentation while collaborating with cross-functional teams to deliver high-quality, reliable data products for the agency.
Plays a key role in implementing the agency's data strategy by developing batch and streaming pipelines, optimizing data warehouse workloads, and enforcing data governance standards. The position assists with requirements gathering, solution reviews, and technical support, and works closely with data architects, scientists, analysts, and project managers to translate business needs into technical designs. This role supports operational processes, contributes to policy and procedure improvements, and may provide mentorship or supervision based on agency needs.
Job Duties
Assists with the data technology strategy, including resolvingstrategic data integration issues, such as data quality and stewardship,real-time,
Event-based data integration, and crafting a universal vision for data integration
Provides direction and oversight for the design and implementation of data solutions for integration and synthesis across multiple secure systems
Assists with the definition, implementation, and continued adherence of new data management policies and design standards for data engineering
Provides advice, training, and technical support for various projects
Participates in project activities such as requirements gathering, solution reviews, and explaining technical complexities to non-technical personnel
Work closely with the solution leads, project managers, data architects, data scientists, and data analysts on solution design, architecture, and implementation
Assists with extraction, transformation, and loading of data from a wide variety of data sources using various data engineering tools and methods.
Designs, builds, and maintains batch and streaming data pipelines in Azure Databricks using Py Spark, Spark SQL, and Delta Lake, following a medallion (bronze/silver/gold) lake house architecture
Develops, loads, and tunes dimensional data models and SQL workloads in Azure Synapse Analytics (dedicated and serverless SQL pools) to support reporting and dashboard needs
Orchestrates and monitors data workflows using Databricks Workflows/Jobs and Synapse or Azure Data Factory pipelines, including scheduling, alerting, and failure recovery
Applies data governance and security controls (e.g., Unity Catalog permissions, role-based access, row- and column-level security, data masking) to protect sensitive health data (PHI/PII) in accordance with HIPAA and agency policy
Assists with documenting and demonstrating solutions by developing documentation, flowcharts, layouts, diagrams, charts, code comments and clear code.
Assists in operations by conducting systems analysis; recommendingchanges in policies and procedures.
The job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Other duties, responsibilities and activities may change or be assigned at any time.
Required/Desired Skills
SkillRequired /DesiredAmountof ExperienceMaster's degree in data science, analytics, informatics, computer science, mathematics, engineering, or related field; OR....Required4YearsBachelor's degree in a related field plus 2+ years of relevant experience; or 4+ years of hands-on experience in a similar data engineering role; OR..Required4YearsRelevant certifications and coursework may substitute for formal education/experience requirementsRequired4YearsDeveloping with Databricks notebooks in PySpark, Spark SQL, and R, including transformations, joins, aggregations, and window functionsRequired4YearsACID transactions, MERGE upserts, schema enforcement/evolution, time travel, and table maintenance (OPTIMIZE, Z-order, VACUUM)Required4YearsWorking with medallion (bronze/silver/gold) architecture and incremental ingestion via Auto Loader, Structured Streaming, or Lakeflow/DLTRequired4YearsUsing Unity Catalog for Workspace Catalogs, schemas, permissions, lineage, external locations, and storage credentialsRequired4YearsRight-sizing clusters and SQL warehouses and diagnose partitioning, shuffle, skew, and caching issues via Spark UIRequired4YearsScheduling and managing dependencies with ADF Pipelines, Databricks Workflows (Jobs), and using Git folders (Repos) for source controlRequired4YearsDesigning MPP warehouse tables, including distribution (hash, round-robin, replicated), columnstore indexes, and partitioningRequired4YearsQuerying Parquet, Delta, and CSV files in ADLS Gen2 using OPENROWSET, external tables, and viewsRequired4YearsBuilding star-schema facts, dimensions, stored procedures, and views, including SCD Type 1 and Type 2Required4YearsDeveloping with COPY INTO, PolyBase, and CETAS, and building parameterized Synapse/ADF pipelines (copy, data flows, triggers)Required4YearsWorkload management, resource classes, statistics, materialized views, result-set caching, and pool scaling/pausingRequired4YearsADLS Gen2 folder/file-format design (Parquet/Delta), Entra ID access control, managed identities, and Key VaultRequired4YearsGit and CI/CD in Azure DevOps or GitHub, including branching, PRs, and deploying Synapse artifacts and Databricks Asset BundlesRequired4YearsMonitoring pipelines and workloads with Azure Monitor/Log Analytics and alerting, and troubleshooting failed jobsRequired4YearsStrong written and verbal communication skillsRequired0Using Microsoft lakehouse patterns, including interoperability and migration paths between Synapse and DatabricksRequired4YearsDatabricks Certified Data Engineer Associate (Databricks Certified Data Engineer Professional a plus)Highly desired0Microsoft Certified: Azure Data Engineer Associate (DP-203) if already heldHighly desired0Power BI connectivity to Synapse (Import vs. DirectQuery) and how model design affects dashboard performanceDesired4Years
Questions
No.QuestionQuestion1Absences greater than two weeks MUST be approved by CAI management in advance, and contact information must be provided to CAI so that the resource can be reached during his or her absence. The Client has the right to dismiss the resource if he or she does not return to work by the agreed upon date. Do you accept this requirement?Question2Please provide the candidate's email address.Question3Candidate must be located in Indiana to be considered for this position. Please provide the city and state where candidate currently resides.Question4Candidate must be paid $43.35 for engagement. The provider markup for this position is 35%. Do you accept this requirement?Question5Resource will be required to work a hybrid schedule being onsite one day per week. Please confirm the resource understands the hybrid schedule. Question6Candidate will be required to work 40 hours per week. Please confirm the resource understand the work hours.Question7Candidate must meet one of the following qualifications: Master's degree in data science, analytics, informatics, computer science, mathematics, engineering, or related field; - a Bachelor's degree in a related field plus 2+ years of relevant experience; or 4+ years of hands-on experience in a similar data engineering role. Relevant certifications and coursework may substitute for formal education/experience requirements.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: RTX1d588d
- Position Id: bf5edbf26c73a9c7d12e7f435d956084
- Posted 2 days ago
