Role: Mid-level Data Engineer

Position Type: Full-Time Contract (40hrs/week)

Contract Duration: Long Term

Work Schedule: 8 hours/day (Mon-Fri)

Location: Hybrid - Hyderabad (Wed and Thursday to be in onsite)

Job Responsibilities:

Develop API-driven systems to govern, manage, and monitor large-scale batch Big Data applications. Build scalable backend services and data engineering solutions that support data processing and operational workflows. Develop and maintain data transformation processes using Spark, SQL, Hive, Python, Scala, and related technologies. Work with AWS cloud services such as S3, EC2, EMR, Lambda, DynamoDB, and API Gateway to build cloud-native data and backend solutions. Build and enhance workflow orchestration using Apache Airflow, including advanced DAG design, dependency management, scheduling, monitoring, and failure handling. Define technical scope, objectives, and implementation approaches by participating in requirements gathering, technical research, and process definition. Participate in architecture reviews, code reviews, performance tuning,



and operational readiness activities. Contribute to test planning and validation for application integrations, functional areas, and project deliverables. Partner with product owners, data engineers, backend engineers, QA, DevOps, and other cross-functional teams to deliver high-quality solutions in an Agile/Scrum setting. Troubleshoot production issues, improve system reliability, and drive automation across data and backend workflows.

Required Qualifications:
- 5+ years of hands-on experience developing enterprise-scale applications, data platforms, or distributed systems.
- 5+ years of experience developing, and operating Big Data platforms and cloud-based infrastructure services, preferably using AWS EMR and the Hadoop ecosystem.
- Hands-on experience with AWS, Spark, Python and/or Scala, Airflow, SQL, Hive, and related data processing technologies.
- Proficiency in either Python or Sca

📌 Mid-level Data Engineer (Hyderabad)
🏢 SkySys
📍 Hyderabad