Data Engineer

Capri Global Capital (CGCL); Gurugram District, Dadri; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Capri Global Capital is seeking an experienced Data Engineer to design, build, and optimize robust data pipelines on AWS, collaborating with data analysts, data scientists, and product teams to power analytics and decision‑making.

Location: Noida or Gurgaon. You will develop ETL/ELT pipelines, data models, and warehousing solutions (Redshift/Snowflake), implement data quality checks, and orchestrate workflows with Airflow or MWAA. Strong Python and SQL skills are essential.

Qualifications

• 4-5 years of hands-on data engineering experience in production environments.
• Strong expertise in AWS data services and cost/performance trade-offs.
• Advanced SQL skills (window functions, CTEs) and Python for data engineering.
• Solid experience with ETL/ELT design patterns, data modeling, and schema evolution.
• Experience with Spark (Glue/EMR) or similar distributed frameworks.
• Proficient with workflow orchestration and CI/CD for data jobs.
• Knowledge of data quality frameworks and data security best practices.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines on AWS.
• Develop and optimize data models, schemas, and data warehouses (Redshift/Snowflake).
• Build data ingestion frameworks for batch and streaming sources.
• Implement data quality checks, validation rules, and monitoring for SLA compliance.
• Write production-grade Python and SQL for data transformations and orchestration.
• Manage data storage, partitioning, and performance tuning.
• Implement orchestration and workflow management (Airflow/MWAA/Step Functions).
• Collaborate with stakeholders to translate business requirements into technical specs.
• Ensure data security, governance, lineage, and compliance.
• Set up observability for pipelines (logging, metrics, alerting) and support on-call rotations.
• Contribute to CI/CD and IaC for data workloads and best practices documentation.

Skills

AWS

Python

SQL

Airflow

ETL/ELT

Data modeling

Big data

Tools

Redshift

Snowflake

Parquet/Delta/Iceberg

Kinesis

MWAA

Docker

ECS/EKS

Job description

Role Description

We are looking for an experienced Data Engineer to design, build, and optimize robust data pipelines and platforms on AWS. You will work closely with data analysts, data scientists, and product teams to deliver reliable, scalable, and secure data solutions that power analytics and decision-making.

Designation: Data Engineer / Senior Data Engineer

Location: Noida / Gurgaon

Job Description

Key Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines and data workflows on AWS

Develop and optimize data models (OLTP/OLAP), schemas, and warehousing solutions (e.g., Redshift, Snowflake, or similar)

Build data ingestion frameworks for batch and streaming data from diverse sources (APIs, RDBMS, files, event streams)

Implement data quality checks, validation rules, and monitoring for data reliability and SLAs

Write efficient, production-grade Python and SQL for data transformations and orchestration

Manage and optimize data storage, partitioning, and performance (query tuning, indexing, cost optimization)

Implement orchestration and workflow management (e.g., Airflow/Step Functions)

Collaborate with stakeholders to translate business requirements into technical specs and data contracts

Ensure data security, governance, lineage, and compliance (IAM, encryption, PII handling)

Set up observability for pipelines (logging, metrics, alerting) and support on-call rotations

Contribute to CI/CD for data workloads, infrastructure-as-code, and best practices documentation

Required Skills and Qualifications

• AWS: S3, Glue, Athena, Lambda, Step Functions, EMR or Glue Spark, Redshift, IAM, CloudWatch, CloudFormation/Terraform


• Programming: Python (pandas, PySpark), SQL (advanced)


• Orchestration: Apache Airflow (or MWAA), Step Functions


• Data Warehousing/Lakes: Redshift, Lake Formation, Parquet/Delta/Iceberg


• Streaming (nice-to-have): Kinesis, MSK (Kafka)


• Containers (nice-to-have): Docker, ECS/EKS

Preferred:

• 4 - 5 years of hands-on data engineering experience in production environments


• Strong expertise in AWS data services and cost/performance trade-offs


• Advanced SQL skills (window functions, CTEs, query tuning) and Python for data engineering


• Solid experience with ETL/ELT design patterns, data modeling (star/snowflake), and schema


• evolution


• Experience with Spark (Glue/EMR) or similar distributed processing frameworks


• Proficiency with workflow orchestration (Airflow or equivalent)


• Practical knowledge of data quality frameworks and automated testing for data pipelines


• Experience with version control (Git) and CI/CD for data jobs


• Strong understanding of security best practices (IAM roles/policies, encryption, VPC, Secrets Manager)