Top Remote Data & Analytics Jobs in Indianapolis, IN

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

Lead analytics engineering for Revenue, Marketing, and Finance by building scalable data solutions, data models, and dashboards; provide training and consultation, support ad hoc data needs, and translate technical findings into executive-level insights to improve operational performance.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Manage performance, reliability, and accountability for high-volume messaging programs. Build dashboards and alerting, run ad hoc analyses, coordinate incident response and vendor testing, conduct post-incident reviews, and maintain documentation and compliance tracking to inform program decisions and improvements.

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Perform data extraction, transformation, validation and visualization to support consumer and commercial analytics. Create and track business metrics, execute strategic analytics projects, deliver accurate results with documentation following audit procedures, and communicate findings with recommendations to stakeholders.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

The Quantitative Researcher will manage yield opportunities, design algorithms, perform risk analysis, and collaborate with engineers on DeFi strategies.

Lead Databricks pre-sales discovery and design Lakehouse architectures, author proposal technical content, run proofs-of-concept, and act as lead architect on major engagements. Own the Databricks partner relationship and co-sell motion, drive certification and internal enablement, resolve performance and governance challenges, and ensure successful production handoffs while building partner-sourced pipeline and scaling the Databricks practice.