Top Data Management Jobs in Indianapolis, IN

Lead managed-data and analytics engagements to build modern data ecosystems, convert insights to strategy, manage client accounts, mentor teams, ensure project delivery and quality, and drive cloud-scale data initiatives.

Lead development and execution of data governance strategies, manage client accounts and deliverables, supervise and mentor teams, analyze data to inform decisions, ensure compliance with firm standards, and identify improvements in data management processes.

Lead development and execution of data-driven strategies, manage project timelines and deliverables, mentor and inspire team members, uphold quality and ethical standards, analyze complex datasets to produce actionable insights, and collaborate on cloud-based data management and advanced analytics initiatives to support client decision-making.

Lead design and implementation of data architecture, data models, and ETL/ELT pipelines across cloud platforms. Manage data warehouses/lakes, enforce data governance and security, mentor and coach teams, partner with stakeholders, and deliver scalable, cost-effective cloud data solutions.

Lead design and delivery of data architectures, pipelines, and BI solutions (AWS/Redshift, DataStage, ETL, SQL Server/DB2). Coach teams, engage stakeholders, apply systems thinking, validate outcomes, and optimize performance under managed services SLAs.

Lead data engineering projects and teams to design, build, and maintain ETL/ELT pipelines, data architectures, and cloud analytics solutions. Use BI tools and cloud platforms to deliver scalable reporting, mentor staff, manage client relationships, and ensure project delivery and performance tuning.

Lead design and implementation of data architecture, build and oversee data pipelines and cloud solutions, ensure governance and security compliance, manage large projects, advise clients strategically, document data models and flows, and coach diverse teams to deliver data engineering best practices.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead development and execution of data governance strategies, supervise and mentor teams, manage client accounts and deliverables, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements to data management processes.

Lead development and execution of data-driven strategies, manage and mentor a data analytics team, oversee project planning and delivery, analyze complex datasets to produce actionable insights, implement cloud data architectures, and support data governance and continuous improvement.

Lead design and delivery of cloud-based data architecture, data models, ETL/ELT pipelines, data warehouses/lakes, and data security. Manage projects, mentor team members, ensure governance compliance, collaborate with stakeholders, and optimize cloud infrastructure for performance, cost, and scalability.

Lead design and implementation of data architecture and cloud-based data engineering solutions. Manage large projects, translate stakeholder requirements into technical designs, ensure data governance and security, develop data models and pipelines, advise clients strategically, and coach teams to deliver operational excellence.

Lead and scale enterprise data governance operations: manage the data domain model and business glossary, run governance council operations, enforce data policies and compliance (SOC 2, GDPR/CCPA), drive catalog adoption and data literacy, and measure governance maturity and ROI through dashboards and remediation workflows.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

Lead a data engineering team building pipelines, transformations, and analytics infrastructure in Azure/AWS/Snowflake. Champion spec-driven, AI-assisted development, ensure secure scalable systems, govern AI-generated code, and partner with product and platform teams.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Lead data engineering strategy and delivery for Orthopedics Supply Chain. Build a scalable lakehouse (Databricks, cloud), enforce governance, data quality, observability, automated testing, and partner with vendors and cross-functional teams to deliver reusable, business-ready data products.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Lead end-to-end delivery of data platform engagements: design and implement scalable ingestion and transformation pipelines, write and review production code (Python/SQL/Scala/Spark), architect cloud environments, advise clients, manage and mentor teams, and support practice development and business development activities.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Lead design and build of a cloud-based data platform; manage and mentor data engineering staff; define engineering standards, data governance, and access controls; partner with stakeholders to deliver scalable, reliable data pipelines and platform services for analytics and AI.

Lead and execute end-to-end ERP data migrations into Dynamics 365 (F&O and CE) for acquisitions. Define migration strategy, design and run ETL, data mapping, reconciliation, validation, and cutover. Manage a blended team, ensure data quality and governance, and drive automation and continuous improvement across migration processes.

Lead a Salesforce data engineering team to design, deliver, and support Salesforce-to-Salesforce integrations and migrations, data modeling, ETL/transformations, automation, and observability. Manage hiring, performance, and career development; partner with stakeholders; adopt AI/LLM agent tooling to automate workflows and improve data quality; reduce technical debt and document systems and processes.

Lead a hands-on data engineering team to build and scale production data pipelines, datasets, and observability for alternative-data products. Drive architecture, data modeling, QA, and AI-ready dataset design while coaching engineers, partnering with product and research, and owning operational excellence across Databricks, Airflow, SQL, and PySpark.