Sr. Data Engineer

Opportunity Overview: We are seeking a Sr. Data Engineer to help drive the technical vision of our Data Engineering team as we scale our infrastructure, services, and architecture. This role is ideal for someone who blends deep technical expertise with strategic thinking and cross-functional influence. As a Sr. Data Engineer, you will partner closely with other data and analytics engineers, architects, product leaders, and business stakeholders to evolve our data infrastructure in support of high-trust, scalable, and business-aligned outcomes. You’ll also serve as a force multiplier across teams; raising the bar for data engineering excellence and accelerating the maturity of our data platform capabilities. What you’ll do: Develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load data from multiple source systems into enterprise data platforms.  Ensure pipelines are scalable, reusable, fault-tolerant, and optimized for batch and near real-time processing requirements. Develop interactive dashboards, scorecards, and KPI reporting solutions using BI tools. Deliver executive, operational, and analytical reporting aligned with business goals. Identify repetitive manual reporting processes and automate them using scripting, workflow orchestration, scheduling tools, and dashboard refresh mechanisms to improve efficiency, accuracy, and turnaround time. Collaborate with internal stakeholders and leadership teams to understand data integration and reporting needs, define KPIs, document business rules, and translate requirements into scalable technical solutions. Implement data validation checks, reconciliation controls, lineage documentation, metadata standards, and governance policies to maintain trusted, secure, and compliant data assets across the organization. Provide technical guidance, code reviews, best practices, and mentor junior team members. Investigate and resolve production incidents related to pipelines, delayed reports, data mismatches, access issues, and system bottlenecks. Perform root cause analysis and implement preventive fixes. Continuously improve platform reliability, performance, scalability, observability, security, and cost efficiency through engineering excellence and proactive monitoring. Required Qualifications: 5+ years of experience in Data Engineering demonstrating expertise in designing scalable data platforms, building robust ETL/ELT pipelines, optimizing data workflows, implementing cloud-based solutions, and delivering reliable, high-performance data systems that support business growth and analytics needs. 5+ years of experience in developing automated data ingestion pipelines that integrate data sourced from multiple streams  into enterprise platforms through cleansing, transformation, validation, and scheduled batch or near real-time processing workflows. Strong proficiency in writing and tuning advanced SQL queries, views, and data models to improve report performance and reduce processing time by monitoring indexing, partitioning, query plans, and database resource utilization. 5+ years of proven expertise in cloud-based, distributed environments (e.g., AWS, EMR, Glue, Iceberg, dbt, Lambda, Athena). Demonstrated experience designing and managing secure client data integrations, including inbound and outbound file exchanges, SFTP transfers, API-based data ingestion, and reliable end-to-end data delivery between client systems and internal platforms. Fluency in modern data architecture patterns, including medallion/lakehouse models, schema evolution, streaming ingestion, and batch orchestration. Familiarity with reporting and dashboarding tools such as AWS QuickSIght or Tableau. Designed and maintained low-latency, high-availability data pipelines to support near real-time processing, timely reporting, and reliable downstream data consumption. Monitored production pipelines and triaged data incidents by performing root cause analysis, resolving failures, fixing data quality issues, and ensuring SLA adherence. Implemented strong data governance, observability, and quality controls including schema validation, lineage tracking, alerting, reconciliation checks, and policy-based access management. Knowledge of CI/CD pipelines, version control, and DevOps practices using GitHub, AWS code pipeline. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline. Ability to commute/relocate: Hyderabad, Telangana: Reliably commute or planning to relocate before starting work (Preferred) Interview Process*: Connect with Talent Acquisition  Meet with the Hiring Manager Behavioral Interview(s) Case Study Interview with Senior Leadership *Subject to change About Cohere Health: Cohere Health’s clinical intelligence platform and agentic AI-powered solutions connect health plans’ strategic goals and providers’ needs, optimizing the speed, cost, and quality of care. With an en