AWS Data Engineer (Spark Scala)

Viraaj HR Solutions Private Limited

3 years

8 - 30 Lacs

Pune Maharashtra India

Posted:1 day ago| Platform:

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Skills Required

aws data spark scala consulting analytics ai design etl latency scalability engineering model automate deployment terraform monitoring coding iam sql strategies git jenkins python orchestration kafka processing certification collaborative devops apache

Work Mode

On-site

Job Type

Full Time

Job Description

Industry & Sector:

Enterprise cloud consulting and data analytics services provider delivering large-scale AWS lakehouse, real-time analytics and AI solutions for global clients.
Role & Responsibilities

Design, build and optimise high-volume data pipelines on AWS using Spark (Scala) and Glue.
Develop reusable ETL frameworks that ingest structured and semi-structured data into S3-based data lakes.
Tune Spark jobs for cost, latency and scalability; implement partitioning, caching and checkpointing best practices.
Collaborate with data scientists to productionise feature engineering and model-output pipelines.
Automate deployment via CloudFormation or Terraform and integrate monitoring with CloudWatch and Prometheus.
Champion coding standards, peer reviews and knowledge sharing across the data engineering guild.

Skills & Qualifications

Must-Have: 3+ years building Spark applications in Scala on AWS; hands-on with Glue, EMR, S3, IAM and Step Functions; proficient in SQL, data modelling and partitioning strategies; version control with Git and CI/CD pipelines (CodePipeline, Jenkins or similar).
Preferred: Experience with Delta Lake or Iceberg table formats; knowledge of Python for orchestration tasks; exposure to streaming (Kafka, Kinesis) and near-real-time processing; certification in AWS Data Analytics or Solutions Architect.

Benefits & Culture Highlights

On-site, engineer-first culture with dedicated R&D sprints and tech conference sponsorship.
Performance-linked bonuses and accelerated promotion paths for high impact.
Collaborative workspace with wellness programs, hack days and flexible leave policy.

Skills: emr,s3,data engineering,python,iceberg,sql,kafka,ci/cd,aws data engineer (spark scala),aws,codepipeline,jenkins,data modelling,git,delta lake,scala,iam,step functions,devops,spark,apache spark,kinesis,glue,partitioning strategies

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AWS Data Engineer (Spark Scala)