Data Engineer

Axis Finance (AFL); Mumbai; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Axis Finance (AFL) is seeking an experienced Data Engineer to design and implement a Data Lake House on AWS, build scalable ETL/ELT pipelines, and collaborate with cross-functional teams to deliver robust data solutions. The role emphasizes data modeling, governance, and secure data integration across on-premise and cloud environments.

The ideal candidate should have 7+ years in data engineering, strong SQL and Python/Java skills, and hands-on experience with AWS services and lakehouse

Qualifications

• 7+ years of data engineering experience, with a focus on cloud data platforms.
• Strong experience with SQL and Python or Java for data processing and transformations.
• Experience with AWS services and data lakehouse architectures.

Responsibilities

• Design, develop, and implement a Data Lake House architecture on AWS, ensuring scalability, flexibility, and performance.
• Build ETL/ELT pipelines for ingesting, transforming, and processing structured and unstructured data.
• Collaborate with cross-functional teams to gather data requirements and deliver data solutions aligned with business needs.
• Develop and manage data models, schemas, and data lakes for analytics, reporting, and BI purposes.
• Implement data governance practices, ensuring data quality, security, and compliance.
• Perform data integration between on-premise and cloud systems using AWS services.
• Monitor and troubleshoot data pipelines and infrastructure for reliability and scalability.

Skills

Data engineering

Cloud data platforms

AWS services

SQL

Python/Java

Data governance

Big data technologies

ETL/ELT

Tools

AWS (S3, Glue, Redshift, Athena, Lambda, IAM, RDS, EC2)

Databricks

Apache Spark

Job description

Dear Candidate

Key Responsibilities:

Should have experience in below

• Design, develop, and implement a Data Lake House architecture on AWS, ensuring scalability, flexibility, and performance.
• Build ETL/ELT pipelines for ingesting, transforming, and processing structured and unstructured data.
• Collaborate with cross-functional teams to gather data requirements and deliver data solutions aligned with business needs.
• Develop and manage data models, schemas, and data lakes for analytics, reporting, and BI purposes.
• Implement data governance practices, ensuring data quality, security, and compliance.
• Perform data integration between on-premise and cloud systems using AWS services.
• Monitor and troubleshoot data pipelines and infrastructure for reliability and scalability.

Skills and Qualifications:

• 7 + years of experience in data engineering, with a focus on cloud data platforms.
• Strong experience with AWS services: S3, Glue, Redshift, Athena, Lambda, IAM, RDS, and EC2.
• Hands-on experience in building data lakes, data warehouses, and lake house architectures.
• Should have experience in ETL/ELT pipelines using tools like AWS Glue, Apache Spark, or similar.
• Expertise in SQL and Python or Java for data processing and transformations.
• Familiarity with data modeling and schema design in cloud environments.
• Understanding of data security and governance practices, including IAM policies and data encryption.
• Experience with big data technologies (e.g., Hadoop, Spark) and data streaming services (e.g., Kinesis, Kafka).
• Have lending domain knowledge will be added advantage

Preferred Skills:

• Experience with Databricks or similar platforms for data engineering.
• Familiarity with DevOps practices for deploying data solutions on AWS (CI/CD pipelines).
• Knowledge of API integration and cloud data migration strategies.