Top Remote Senior Level Data Engineering Jobs in Indianapolis, IN

The Data Engineer will design and maintain data models on Snowflake, enforce data standards, manage security, optimize SQL, implement CI/CD, and mentor junior staff.

Lead and mentor a Data Engineering team, manage data operations, ensure compliance with HIPAA, and design scalable ETL pipelines while collaborating across departments.

The Lead Analytics Engineer will model revenue, specifically subscription revenue, manage financial KPIs, and ensure reconciliation with source systems like Stripe, while adhering to data governance standards.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

The Energy Analyst will enhance data systems for market data utilization, collaborating with engineers to improve data handling and quality assurance processes, driven by a passion for clean energy.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

Manage leased partner network data integration into I-Network, ensure data quality and delivery for client claims systems and regulatory filing, support SFTP access, create requirements and QA sign-off for projects, produce analytical insights, mentor team members, and assist Business Development/National Accounts and project management.

Lead legacy-to-SaaS data migrations: design and execute ETL, extract/transform/load data, validate integrity, map business workflows to target models, engage clients, document processes, support governance, and train stakeholders to ensure accurate, secure conversions.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.