Data Scientist

Data Scientist
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Indianapolis, IN (One day in office 4 days remote)
Master's degree in data science, analytics, informatics, computer science, mathematics, engineering, or related field; ...orBachelor'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..Relevant certifications and coursework may substitute for formal education/experience requirementsDeveloping with Databricks notebooks in PySpark, Spark SQL, and R, including transformations, joins, aggregations, and window functionsACID transactions, MERGE upserts, schema enforcement/evolution, time travel, and table maintenance (OPTIMIZE, Z-order, VACUUM)Working with medallion (bronze/silver/gold) architecture and incremental ingestion via Auto Loader, Structured Streaming, or Lakeflow/DLTUsing Unity Catalog for Workspace Catalogs, schemas, permissions, lineage, external locations, and storage credentialsRight-sizing clusters and SQL warehouses and diagnose partitioning, shuffle, skew, and caching issues via Spark UIScheduling and managing dependencies with ADF Pipelines, Databricks Workflows (Jobs), and using Git folders (Repos) for source controlDesigning MPP warehouse tables, including distribution (hash, round-robin, replicated), column store indexes, and partitioningQuerying Parquet, Delta, and CSV files in ADLS Gen2 using OPENROWSET, external tables, and viewsBuilding star-schema facts, dimensions, stored procedures, and views, including SCD Type 1 and Type 2Developing with COPY INTO, PolyBase, and CETAS, and building parameterized Synapse/ADF pipelines (copy, data flows, triggers)Workload management, resource classes, statistics, materialized views, result-set caching, and pool scaling/pausingADLS Gen2 folder/file-format design (Parquet/Delta), Entra ID access control, managed identities, and Key VaultGit and CI/CD in Azure DevOps or GitHub, including branching, PRs, and deploying xzbcwsv Synapse artifacts and Databricks Asset BundlesMonitoring pipelines and workloads with Azure Monitor/Log Analytics and alerting, and troubleshooting failed jobsStrong written and verbal communication skillUsing Microsoft lakehouse patterns, including interoperability and migration paths between Synapse and DatabricksDatabricks Certified Data Engineer Associate (Databricks Certified Data Engineer Professional a plus)Microsoft Certified: Azure Data Engineer Associate (DP-203) if already heldPower BI connectivity to Synapse (Import vs. DirectQuery) and how model design affects dashboard performance