Data Scientist (Ref: 18830)

Position:  Data Scientist (Ref: 18830)

Location:  Indianapolis, IN USA, 46204

Salary:  $43.35/hr.

Duration:  1 Years 2 Months 9 Days - Contract

Openings:  1

Deadline:  10/28/2026

Description:

***Local Candidates

***Hybrid

We are seeking an experienced Data Scientist / Data Engineer to design, build, and maintain secure, scalable data solutions across cloud analytics platforms. This role plays a key part in advancing enterprise data strategy by developing batch and streaming pipelines, optimizing data warehouse workloads, and enforcing rigorous data governance standards.

You will collaborate closely with data architects, analysts, and project managers to translate business needs into technical designs, supporting data integration, dimensional modeling, and end-to-end data delivery.

Key Responsibilities

• Data Pipeline Engineering: Design, build, and maintain batch and streaming data pipelines in Azure Databricks using PySpark, Spark SQL, and Delta Lake, following a medallion (Bronze/Silver/Gold) lakehouse architecture.
• Data Warehousing & Modeling: Develop, load, and tune dimensional data models and SQL workloads in Azure Synapse Analytics (both dedicated and serverless SQL pools) to support enterprise dashboards and reporting.
• Workflow Orchestration: Orchestrate, schedule, and monitor workflows using Databricks Workflows/Jobs and Azure Data Factory / Synapse pipelines, ensuring alerting, monitoring, and failure recovery.
• Data Governance & Security: Implement and enforce strict governance policies, role-based access control, Unity Catalog permissions, row- and column-level security, and data masking to safeguard sensitive data (PHI/PII) in compliance with regulatory and HIPAA standards.
• Integration Strategy & Support: Assist with the broader data technology strategy, addressing data stewardship, quality control, event-driven integration, and universal integration frameworks.
• Cross-Functional Collaboration: Partner with solution leads, architects, and business stakeholders during requirements gathering, solution architecture reviews, and technical demonstrations.
• Documentation & Continuous Improvement: Maintain comprehensive technical documentation, architecture diagrams, data flowcharts, and clear code comments while recommending operational and process improvements.

Experience & Qualifications

• Strong, hands-on experience designing and deploying cloud data architectures utilizing Azure Databricks and Azure Synapse Analytics.
• Deep proficiency in PySpark, Spark SQL, and Delta Lake architectures.
• Proven experience building and managing ETL/ELT pipelines using Azure Data Factory or Databricks Workflows.
• Solid foundation in dimensional data modeling and SQL performance tuning.
• Direct experience handling sensitive regulatory datasets (PHI/PII) and implementing compliance/governance standards (e.g., Unity Catalog, HIPAA).
• Ability to work effectively in a hybrid schedule in Indianapolis, IN.
• Location: Indianapolis, IN (Hybrid – Local candidates only)
• Position Type: Contract
• Interview Type: Webcam

Required / Desired Skills

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