Cloud Data Engineer - Data Pipeline and Quality

Thakral One; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Thakral One in Bengaluru is looking for a Cloud Data Engineer to design and optimise data solutions for financial institutions. The role involves managing data analysis and integration across systems, ensuring data quality, and building high-performance data pipelines using AWS services and advanced analytical techniques.

The ideal candidate will have over 5 years of Data Engineering experience, strong proficiency in AWS, and familiarity with data lakes and the financial industry.

Qualifications

• 5+ years of experience as a Data Engineer.
• Proficiency in AWS services and building data pipelines.
• Experience in the financial services industry is preferred.

Responsibilities

• Design, build, and optimise data warehouses and lakes.
• Manage data analysis and integration across systems.
• Ensure data quality and implement validation processes.

Skills

Data pipeline building

AWS services (Glue, Redshift, etc.)

Data analysis and integration

Big data processing

Collaboration within teams

Education

Bachelor's degree in IT or related field

Tools

AWS

Informatica

Snowflake

Spark

Job description

Cloud Data Engineer - Data Pipeline and Quality

As a Cloud Data Engineer, you will design, build, and optimise data warehouses, data lakes, and data marts for large financial institutions. You will work closely with technology and business leads to enhance critical enterprise applications across on‑prem environments and AWS, leveraging the Modern Data Stack including Snowflake and Starburst to deliver scalable, high‑quality data solutions.

What You'll Do and How You'll Succeed

• Manage data analysis and integration across disparate systems.
• Translate functional specifications from business users into technical designs for implementation and deployment.
• Extract, transform, and load large volumes of structured and unstructured data into AWS data lakes or data warehouses.
• Work with cross‑functional teams to develop prototypes, produce design artefacts, develop components, support SIT and UAT testing, triage issues, and perform bug fixing.
• Optimise and fine‑tune data pipeline jobs for performance and scalability.
• Implement data quality and validation processes to ensure data accuracy and integrity.
• Provide problem‑solving expertise and perform complex analysis to design business intelligence integrations.
• Convert physical data integration models and design specifications into source code.
• Ensure high performance and quality of data integration systems to meet business requirements.

We'd Love to Hear From You If

Experience

• You have a bachelor's degree in IT, Information Systems, Computer Science, Software Engineering, or a related field.
• You have 5+ years of experience as a Data Engineer, with strong experience building data pipelines and processing large datasets.
• You have experience working with data lakes, data warehouses, and distributed computing systems.
• You have experience in the financial services or banking industry (preferred).

Technical Expertise

• You have 5+ years of strong proficiency in AWS services such as AWS Glue, Redshift, EMR, RDS, Kinesis, S3, Athena, DynamoDB, Step Functions, and Lambda.
• You have 3+ years of experience with Informatica for building data pipelines.
• You have 2+ years of experience with Snowflake Data Platform (highly desirable).
• You have exposure to data virtualisation platforms such as Starburst or Denodo.
• You are skilled in HiveQL, Python, Spark, Scala, and big data processing.
• You understand data modelling, database design, and ETL principles.
• You are familiar with data governance, data security, and cloud compliance practices.
• You can optimise and fine‑tune Spark jobs and data pipelines for performance.
• AWS data‑related certifications are a plus.

Ways of Working

• You communicate effectively and collaborate well within cross‑functional teams.
• You are committed to high‑quality delivery, continuous improvement, and elegant solution design.
• You approach problem‑solving with analytical depth and technical rigour.