Job Title : Tech Lead – Data Lake Platform

Number of Positions : 2

Experience : 7+ Years

Role Type : Technical Lead / Data Platform Lead

Domain : Data Engineering / Data Platform / AWS

About the Role :

We are looking for an experienced Tech Lead – Data Lake Platform to lead the design, development, and operations of an enterprise-scale AWS-based Data Lake Platform.

The platform will ingest data from multiple business systems, process it through structured data layers, and serve data for analytics, reporting, APIs, and operational applications.

As a Tech Lead, you will be responsible for setting the technical direction, leading data engineering teams, driving platform reliability and performance, and owning the platform's delivery, governance, and production support end to end.

Core Tech Stack :

AWS | S3 | EMR | Glue | Athena | Redshift | DMS | Lambda | RDS | IAM | Airflow | Spark/PySpark | SQL | Data Modeling | Hasura | GraphQL | DBT | PostgreSQL/Aurora | Kafka

Key Responsibilities :

- Own the overall Data Lake Platform architecture, covering data ingestion, staging, curated layers, consumption, analytics, and API/data serving.
- Lead the design and development of production-grade data pipelines using AWS Glue, EMR/Spark, Airflow, DBT, Athena, and Redshift.
- Design scalable batch and analytics pipelines with a focus on reliability, performance, data quality, and maintainability.
- Own the API/data-serving architecture from consumption data → RDS/PostgreSQL → Hasura GraphQL → Lambda/API Gateway.
- Drive improvements in platform stability, including orchestration failures, cluster sizing, pipeline SLAs, query performance, and production reliability.
- Design and implement appropriate AWS security, access control, IAM, PII handling, and data governance practices.




- Lead technical discussions, architecture decisions, code reviews, and engineering best practices.
- Mentor and guide data engineers while ensuring high-quality and scalable engineering delivery.
- Own production support, incident management, troubleshooting, and root-cause analysis (RCA) for critical data platform issues.
- Develop and maintain runbooks, operational procedures, monitoring, and incident response practices.
- Collaborate with business, product, application, and analytics teams to onboard new datasets and support reporting, API, and data consumption requirements.
- Ensure the platform meets defined availability, performance, security, data quality, and compliance requirements.

Must-Have Skills :

- 7+ years of experience in Data Engineering, Data Platform Engineering, or related areas, including experience in technical leadership or architecture.
- Strong hands-on experience with AWS Data Services, including:
- Amazon S3
- AWS EMR
- AWS Glue
- Amazon Athena
- Amazon Redshift
- AWS DMS
- AWS Lambda
- Amazon RDS
- AWS IAM
- Strong production experience with Apache Airflow.
- Robust hands-on experience with Apache Spark / PySpark.
- Strong SQL skills and experience with data modeling, including layered data architecture, data marts, and enterprise data models.
- Experience with Hasura or a similar GraphQL layer for PostgreSQL-based data/API serving.




- Strong understanding of data lake architecture and enterprise data platforms.
- Proven experience leading engineers and driving technical decisions.
- Hands-on experience with production support, troubleshooting, incident management, and RCA.
- Strong understanding of data platform performance, scalability, reliability, and SLA management.

Good-to-Have Skills :

- Experience with DBT and modern data transformation practices.
- Experience with lakehouse table formats on Amazon S3, such as Apache Iceberg or similar technologies.
- Strong knowledge of Amazon Redshift workload optimization, including :
- Distribution keys
- Sort keys
- Spectrum
- External tables
- Experience with Kafka or other streaming/data ingestion technologies.
- Experience with PostgreSQL / Amazon Aurora as a data-serving layer.
- Experience with Lambda and API Gateway for API-based data serving.
- Experience with enterprise data governance, data quality, security, and compliance.
- Experience in BFSI / Banking / Financial Services / Insurance domain.

Ideal Candidate :

The ideal candidate is a hands-on Data Platform / Data Engineering Lead who can operate at both the architecture and implementation level. You should be comfortable designing an AWS Data Lake from end to end, leading engineers, troubleshooting production issues, and working closely with business and application teams to deliver reliable data products.

Skills:- Amazon Web Services (AWS), Amazon S3, Amazon EMR, athena, Amazon Redshift, DMS, AWS Lambda, AWS RDS, Amazon RDS, AWS IAM, Apache Airflow, Spark, PySpark, SQL, Data modeling, hasura, GraphQL, Data Transformation Tool (DBT), PostgreSQL, Apache Aurora, Apache Kafka and Data Lake Platform

📌 Tech Lead – Data Lake Platform (Gurugram)
🏢 NeogenCode Technologies
📍 Gurugram