Data Engineer (Contract)

Data Engineer (Contract) Location: India, Hyderabad

Work Experience: 7+ Years

• Hands-on data engineering experience building and supporting production data pipelines.
• Strong SQL skills (design, tuning, troubleshooting) and experience working with relational and analytical data stores.
• 3+ years of coding/scripting experience with Python (Java/Scala a plus).
• 3+ years of experience on AWS (e.g., S3, Glue, EMR, Lambda, IAM, CloudWatch, MWAA/Airflow).
• 2+ years of experience with infrastructure-as-code and CI/CD practices (Terraform preferred).
• 2+ years of experience with Spark; streaming experience with Kafka is a plus.
• Experience leveraging AI tools (e.g., GenAI assistants) to improve productivity, with an understanding of secure and responsible usage.
• Self-driven, delivery-focused, and comfortable working in a contract environment with clear milestones and timelines.
• Curious and methodical, able to research new data sources, open-source tools, and ingestion patterns to propose practical approaches.
• Strong operational mindset: observability, alerting, incident response, and continuous improvement to reduce pipeline failures.
• Clear communicator with strong stakeholder management skills; able to surface risks early and provide crisp status updates.
• Familiarity with domain areas such as Portfolio Management, Cyber Security, and ServiceNow reporting is a plus.

Qualifications: Bachelors or Masters degree in Computer Science, Information Technology, or a related field.

• Build and enhance ELT/ETL pipelines to ingest, transform, and curate data from multiple sources into clean, trusted datasets.
• Develop and maintain data processing jobs using Spark and Python, with a focus on performance and reliability.
• Implement and monitor data quality checks, reconcile issues, and partner with analysts to resolve data defects.
• Translate requirements into technical tasks and deliver well-documented solutions, including runbooks and operational playbooks.
• Support day-to-day operations of data pipelines-monitoring, incident triage, root-cause analysis, and meeting SLA targets.
• Develop workflows and scheduling using MWAA (Airflow) and AWS-native services.
• Collaborate effectively across time zones with onsite stakeholders and the India engineering team through clear communication and proactive status updates.