Data Engineer

Industry & Sector:  HR Services & People Analytics — delivering talent management, recruitment analytics, and workforce insights for enterprise customers. This is an on-site data engineering role in India, focused on building reliable data platforms and pipelines that power HR analytics, reporting, and data-driven talent products.

Primary

Title:

Data Engineer (On-site, India)

Role & Responsibilities

Design, build and maintain scalable ETL/ELT pipelines to ingest, transform and deliver HR and operational data from multiple sources into the analytics platform.
Develop and optimise data models and data warehouse schemas to enable fast, reliable reporting and analytics for HR systems and BI consumers.
Implement batch and streaming data solutions; ensure data quality, lineage, and observability across pipelines.
Collaborate with data scientists, analytics, and product teams to translate business requirements into performant data solutions and reliable APIs.
Author reusable engineering patterns, CI/CD pipelines, and monitoring/alerting for production data services; drive automation and deployment best practices.
Troubleshoot production incidents, tune performance, and enforce data governance, security, and compliance practices for on-site infrastructure.

Skills & Qualifications

Must-Have

Proven experience building production ETL/ELT pipelines using Python and SQL.
Hands-on with Apache Spark for large-scale data processing and optimisation.
Experience designing and scheduling workflows with Apache Airflow (or equivalent orchestrators).
Strong understanding of data modelling, dimensional modelling, and data warehousing principles.
Operational experience on a cloud platform (AWS preferred) including S3, EMR/Glue, RDS/Redshift or similar.
Familiarity with data quality frameworks, observability, and production troubleshooting practices.

Preferred

Experience with streaming platforms (Apache Kafka or similar).
Hands-on with modern analytics stacks like dbt or Snowflake.
Knowledge of containerisation and orchestration (Docker, Kubernetes) and CI/CD for data workloads.

Benefits & Culture Highlights

On-site team environment with mentoring, hands-on learning, and clear career progression in data engineering.
Opportunity to work on end-to-end HR analytics products that directly impact enterprise customers.
Competitive compensation, professional development support, and a culture focused on engineering excellence.

If you are a pragmatic data engineer who thrives in on-site, delivery-focused environments and wants to build high-quality data platforms for HR analytics, apply now with your CV and relevant project highlights.

Skills:

gcp,data modeling,aws,azure,data warehousing,data engineering,apache spark,python,sql