Eli Lilly and Company

Data Engineer – Operations

Eli Lilly and Company

full-time

Posted on:

Location Type: Office

Location: Hyderabad • 🇮🇳 India

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Job Level

JuniorMid-Level

Tech Stack

AirflowAmazon RedshiftApacheAWSAzureCloudETLGrafanaPrometheusPySparkPythonSQL

About the role

  • Monitor and manage day-to-day operations of data pipelines, ETL jobs, and cloud-native data platforms (e.g., AWS, Databricks, Redshift).
  • Own incident response and resolution, including root cause analysis and post-mortem reporting for data failures and performance issues.
  • Perform regular system health checks, capacity planning, and cost optimization across operational environments.
  • Maintain and enhance logging, alerting, and monitoring frameworks using tools like CloudWatch, Datadog, Prometheus, etc.
  • Collaborate with development teams to operationalize new data workflows, including CI/CD deployment, scheduling, and support documentation.
  • Ensure data quality by executing validation checks, recon processes, and business rule compliance.
  • Work with vendors (if applicable) and internal teams to support migrations, upgrades, and production releases.

Requirements

  • Strong background in managing and maintaining data pipelines, preferably in AWS or Azure environments.
  • Proficiency in SQL, Python, or PySpark for operational debugging and performance tuning.
  • Hands-on experience with monitoring tools (e.g., CloudWatch, Datadog) and orchestration frameworks like Airflow.
  • Familiarity with CI/CD processes and code deployment practices using GitHub or similar tools.
  • Awareness of data governance, privacy, and security protocols.
  • Proactive problem-solving mindset with the ability to identify patterns in recurring issues.
  • Exposure to AI/ML concepts or a passion for learning and applying automation through AI frameworks.
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
  • 2 - 12 years of experience in Data Engineering, DataOps, Platform Reliability, or equivalent roles.
  • Hands-on experience managing pipelines on Databricks, AWS Glue, EMR, Snowflake, or similar platforms.
  • Strong scripting skills (Python, Bash) and familiarity with version control (Git).
  • Experience with orchestration tools like Apache Airflow, AWS Step Functions, or similar.
  • Exposure to monitoring/observability tools like CloudWatch, Datadog, Grafana, Prometheus, etc.
  • Solid understanding of data lifecycle, job dependencies, and data validation techniques.
  • Eagerness to learn and apply AI/ML approaches in operational workflows.
Benefits
  • Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions.
  • If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form for further assistance.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
SQLPythonPySparkBashAWSAzureDatabricksAirflowGitData validation
Soft skills
Proactive problem-solvingCollaborationCommunicationPattern identificationEagerness to learn
Certifications
Bachelor's degree in Computer ScienceBachelor's degree in EngineeringBachelor's degree in Information Systems