Quick Overview
Seniority
Mid Senior
Work mode
On Site
Location
Indianapolis, IN, United States
Posted
Yesterday
SQLGitApache SparkDatabricksHIPAAUnityVaultAzurePower BICI/CDAzure DevOpsAzure Data FactoryDelta Lake
Job Description
Job Title: Senior Azure Databricks Data Engineer
Location: Indianapolis, IN (Hybrid)-Onsite one day per week. Local candidates
Position Type: Contract
Interview Mode: Web Cam
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
|
Skill
|
Required /Desired
|
Amount
|
Actual Years of Experience
|
|
Master's degree in data science, analytics, informatics, computer science, mathematics, engineering, or related field; OR....
|
Required
|
4
|
|
|
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; OR..
|
Required
|
4
|
|
|
Relevant certifications and coursework may substitute for formal education/experience requirements
|
Required
|
4
|
|
|
Developing with Databricks notebooks in PySpark, Spark SQL, and R, including transformations, joins, aggregations, and window functions
|
Required
|
4
|
|
|
ACID transactions, MERGE upserts, schema enforcement/evolution, time travel, and table maintenance (OPTIMIZE, Z-order, VACUUM)
|
Required
|
4
|
|
|
Working with medallion (bronze/silver/gold) architecture and incremental ingestion via Auto Loader, Structured Streaming, or Lakeflow/DLT
|
Required
|
4
|
|
|
Using Unity Catalog for Workspace Catalogs, schemas, permissions, lineage, external locations, and storage credentials
|
Required
|
4
|
|
|
Right-sizing clusters and SQL warehouses and diagnose partitioning, shuffle, skew, and caching issues via Spark UI
|
Required
|
4
|
|
|
Scheduling and managing dependencies with ADF Pipelines, Databricks Workflows (Jobs), and using Git folders (Repos) for source control
|
Required
|
4
|
|
|
Designing MPP warehouse tables, including distribution (hash, round-robin, replicated), columnstore indexes, and partitioning
|
Required
|
4
|
|
|
Querying Parquet, Delta, and CSV files in ADLS Gen2 using OPENROWSET, external tables, and views
|
Required
|
4
|
|
|
Building star-schema facts, dimensions, stored procedures, and views, including SCD Type 1 and Type 2
|
Required
|
4
|
|
|
Developing with COPY INTO, PolyBase, and CETAS, and building parameterized Synapse/ADF pipelines (copy, data flows, triggers)
|
Required
|
4
|
|
|
Workload management, resource classes, statistics, materialized views, result-set caching, and pool scaling/pausing
|
Required
|
4
|
|
|
ADLS Gen2 folder/file-format design (Parquet/Delta), Entra ID access control, managed identities, and Key Vault
|
Required
|
4
|
|
|
Git and CI/CD in Azure DevOps or GitHub, including branching, PRs, and deploying Synapse artifacts and Databricks Asset Bundles
|
Required
|
4
|
|
|
Monitoring pipelines and workloads with Azure Monitor/Log Analytics and alerting, and troubleshooting failed jobs
|
Required
|
4
|
|
|
Strong written and verbal communication skills
|
Required
|
||
|
Using Microsoft lakehouse patterns, including interoperability and migration paths between Synapse and Databricks
|
Required
|
4
|
|
|
Databricks Certified Data Engineer Associate (Databricks Certified Data Engineer Professional a plus)
|
Highly desired
|
||
|
Microsoft Certified: Azure Data Engineer Associate (DP-203) if already held
|
Highly desired
|
||
|
Power BI connectivity to Synapse (Import vs. DirectQuery) and how model design affects dashboard performance
|
Desired
|
4
|
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