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Job Description
ETL Developer / Senior Data Engineer
Company: Insight Global (on behalf of our client)
Location: Remote (must be able to go onsite in Hyderabad for background screening)
Start Date: Immediate
Availability: Must be able to start within 2–3 weeks
Notice Period: ASAP hire – only apply if you can start within 2 weeks of offer
Interview Process: Priority given to candidates who message on with their resume
Hiring Priority: Immediate joiners only
About the Role
Insight Global’s client is seeking a Senior ETL / Data Engineer to design, build, and optimize scalable data pipelines within an AWS-based data platform. This role focuses on high-performance ETL workflows using Databricks, Apache Spark, and AWS-native data services, supporting enterprise analytics and data-driven initiatives.
Required Skills & Experience
- 7–10 years of hands-on ETL and data engineering experience
- Strong expertise with Databricks and Apache Spark
- Solid experience with AWS data services, including Glue, S3, Lambda, EMR, Athena, and Secrets Manager
- Advanced SQL skills with experience across both relational and NoSQL data stores
- Experience with CI/CD pipelines, Git, and modern data engineering best practices
- Strong debugging, performance tuning, and ETL pipeline optimization skills
Nice to Have
- Experience with Python and/or Scala for data workflows
- Familiarity with AWS orchestration and messaging services (Kinesis, SNS/SQS, CloudWatch)
- Experience implementing data quality frameworks and data lineage
- Exposure to large-scale, enterprise analytics initiatives
- Knowledge of data modeling and job optimization techniques
Responsibilities
- Design, build, and maintain scalable ETL pipelines in an AWS-based ecosystem
- Develop and optimize high-performance data workflows using Databricks and Spark
- Ingest, transform, and integrate structured and unstructured data sources
- Implement monitoring, alerting, and data quality frameworks to ensure reliability
- Optimize pipeline performance, cost, and scalability
- Collaborate with U.S.-based stakeholders to deliver robust, production-ready data solutions
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