Build and maintain scalable AWS data platforms and ETL/ELT pipelines using SQL, Python, Spark, and AWS services. Develop data lakes, warehouses, ingestion workflows, transformations, and analytics-ready data models. Monitor pipeline performance, reliability, security, and data quality; troubleshoot issues and conduct root-cause analysis. Collaborate with architects, DevOps, QA, product teams, and business stakeholders while contributing to documentation, code reviews, and engineering best practices.
Job Description:
Job Description – Data Engineer (AWS)1. Basic Information
- Job Title: Data Engineer (AWS)
- Experience: 3 to 7 Years
We are looking for a hands-on Data Engineer – AWS with 3 to 7 years of experience in developing, building, and maintaining scalable, secure, and high-performance data platforms on AWS.
This is an individual contributor role focused on data pipeline development, cloud data engineering, and analytics enablement. The candidate should have strong hands-on expertise in AWS data services, SQL, and Python, along with experience in building reliable batch and streaming pipelines in a global delivery environment.
3. Must-Have SkillsCloud & Data Engineering (AWS)- Strong hands-on experience with:
- Amazon S3
- AWS Glue
- Amazon Athena
- Amazon Redshift
- Amazon EMR
- Experience designing cloud-native data lakes and data warehouse architectures
- Solid understanding of batch data processing and basic exposure to streaming concepts
Strong SQL skills (mandatory):
- Complex queries, joins, aggregations, and transformations
- Experience working with large datasets in Redshift/Athena
Strong Python skills (mandatory):
- Python for data engineering and ETL use cases
- Experience with PySpark / Spark (preferred)
Good understanding of:
- Data modeling
- Transformations
- Performance tuning
- Hands-on experience with Spark / PySpark
- Experience handling:
- Structured and semi-structured data
- Knowledge of:
- Schema evolution
- Data quality checks
- Validation logic
- Working knowledge of Infrastructure as Code (Terraform / CloudFormation)
- Basic experience with CI/CD pipelines for data workloads
- Understanding of logging and monitoring using AWS CloudWatch
- Ability to work with architects, DevOps, QA, and business stakeholders
- Good communication skills to clearly explain technical concepts
- Experience with streaming technologies (Amazon Kinesis / Kafka)
- Familiarity with Lakehouse and modern data platform architectures
- Integration experience with BI / reporting tools
- Basic knowledge of:
- Data governance
- Data quality
- Metadata management
- Awareness of AWS cost optimization (FinOps basics)
- Experience in Agile delivery models with global teams
- Exposure to AI / ML use cases
- Design and build scalable ETL/ELT pipelines on AWS
- Develop:
- SQL-based data transformations
- Python-based data pipelines
- Implement data ingestion pipelines using S3, Glue, EMR
- Build data models optimized for analytics, performance, and cost efficiency
- Support deployment and execution of data pipelines
- Monitor:
- Pipeline performance
- Reliability
- Data quality
- Troubleshoot data issues and perform root cause analysis
- Apply best practices for:
- Security
- Reliability
- Scalability
- Work with architects and product teams to understand requirements
- Translate business needs into AWS data engineering solutions
- Contribute to:
- Documentation
- Code reviews
- Engineering best practices
- Bachelor’s or Master’s degree (or equivalent) in:
- Computer Science
- Information Technology
- Data Engineering
- or related field
- AWS Certified:
- Solutions Architect
- DevOps (Professional)
- Snowflake Core Certification (optional)
Location:
DGS India - Mumbai - Goregaon Prism TowerBrand:
MerkleTime Type:
Full timeContract Type:
PermanentSimilar Jobs
Automotive
Leads data engineering teams responsible for designing, developing, deploying, and maintaining scalable data pipelines, integrations, platforms, and analytical solutions. Oversees data architecture, governance, security, performance, reliability, cost optimization, and cloud or distributed computing environments. Partners with architects, analysts, IT teams, and business stakeholders to deliver trusted data. Mentors engineers, manages team budgets and forecasts, supports continuous improvement, and provides technical guidance on complex data engineering problems.
Top Skills:
AgileAIApache HiveApache KafkaSparkCi/CdCloud Data PlatformsData WarehousingDevsecopsDistributed ComputingETLInfrastructure As CodeJavaMicrosoft CopilotPythonSQL
Automotive
Leads data engineering teams responsible for scalable pipelines, integrations, data platforms, modeling, warehouses, and analytics solutions. Partners with architects, analysts, business stakeholders, and IT teams to deliver secure, governed, high-performance data capabilities. Oversees reliability, optimization, cloud and distributed processing, continuous improvement, and emerging AI-enabled productivity. Mentors engineers, resolves complex technical issues, manages team budgets and forecasts, and ensures timely, accurate data availability.
Top Skills:
AgileAIApache HiveApache KafkaSparkAutomated TestingCi/CdCloud ComputingCloud Data ServicesCo-PilotData WarehousesDatabase SystemsDevsecopsDistributed ComputingETLInfrastructure As CodeJavaPythonSQL
AdTech • Marketing Tech • Software
Build and maintain scalable AWS data platforms, including cloud-native data lakes, warehouses, and reliable batch or streaming pipelines. Develop SQL transformations and Python-based ETL using services such as S3, Glue, EMR, Redshift, and Athena. Monitor pipeline performance, reliability, and data quality; troubleshoot issues and apply security, scalability, and cost-efficiency best practices. Collaborate with architects, DevOps, QA, product teams, and business stakeholders while contributing to documentation, code reviews, and delivery standards.
Top Skills:
Amazon AthenaAmazon CloudwatchAmazon EmrAmazon KinesisAmazon RedshiftAmazon S3Apache KafkaSparkAWSAws CloudformationAws GlueCi/CdPysparkPythonSnowflakeSQLTerraform
What you need to know about the Pune Tech Scene
Once a far-out concept, AI is now a tangible force reshaping industries and economies worldwide. While its adoption will automate some roles, AI has created more jobs than it has displaced, with an expected 97 million new roles to be created in the coming years. This is especially true in cities like Pune, which is emerging as a hub for companies eager to leverage this technology to develop solutions that simplify and improve lives in sectors such as education, healthcare, finance, e-commerce and more.
