Jobs›Tech Data, Gurugram

Tech Lead – Data Lake Platform

NeoGenCode Technologies Pvt Ltd · Gurugram
Senior
Pay₹12L–18La year, as listed
WhereGurugramHaryana
TypeFull time7-12 years
Posted7 Oct2 days ago, via the company site
Kaam checked
No fee, deposit or pay-to-apply signs
Day work
No vehicle or licence needed
Skills they list22 named
Amazon Web Services (AWS)Amazon S3Amazon EMRathenaAmazon RedshiftDMSAWS LambdaAWS RDSAmazon RDSAWS IAMApache AirflowSparkPySparkSQLData modelinghasuraGraphQLData Transformation Tool (DBT)PostgreSQLApache AuroraApache KafkaData Lake Platform
About this job
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.

Strong 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.

Never pay to get work. If a listing asks for a fee, it is a scam. The ten signs →

Apply on the company site
Opens cutshort.io in a new tab