Data Platform Modernization Engineer - Junior (Databricks)

Location: Bangalore, KA, IN

Req ID: 392928

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Data Platform Modernization Engineer - Junior (Databricks) to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

We are seeking a hands-on Data Engineer / Developer with 3–6 years of experience to support an enterprise data platform modernization initiative. The role will focus on migrating legacy Informatica PowerCenter and AWS Glue workloads to Databricks and developing scalable, reliable data pipelines using established migration patterns and common frameworks.

The ideal candidate should have strong hands-on development skills in PySpark, Python, SQL and Databricks, with experience in ETL development, data transformation, testing and troubleshooting.

Day-to-Day Job Duties

Analyze existing Informatica workflows, mappings and AWS Glue jobs to understand source-to-target mappings and transformation logic.

Develop Databricks notebooks and data pipelines to migrate existing ETL workloads to the Databricks Lakehouse.

Develop data transformations using Python, PySpark, Spark SQL and Databricks SQL.

Implement Bronze, Silver and Gold layer processing following established project architecture and coding patterns.

Develop batch and incremental processing pipelines using Delta Lake and established watermark/control mechanisms.

Develop and maintain Databricks Jobs/Workflows and Lakeflow Declarative Pipelines as required.

Reuse common project frameworks for logging, auditing, data quality, error handling and notifications.

Convert Informatica transformations, mappings, lookups and business rules into equivalent Databricks implementations while preserving existing business logic.

Support migration of AWS Glue jobs and database-based processing into Databricks.

Perform unit testing and source-to-target data reconciliation for migrated pipelines.

Investigate and resolve data, SQL, PySpark and pipeline execution issues.

Support integration testing, regression testing, UAT and production validation.

Work with senior developers and technical leads to resolve technical issues and dependencies.

Follow established coding, performance, security and development standards.

Participate in code reviews and incorporate review feedback.

Prepare technical documentation and support knowledge transfer for migrated workloads.

Support deployment, monitoring, production stabilization and cutover activities.

Basic Qualifications

3–6 years of experience in data engineering, ETL development or application/data platform development.

Hands-on experience with Databricks and Apache Spark.

Strong development skills in Python/PySpark and SQL.

Experience with

Databricks notebooks

Spark SQL / Databricks SQL

Delta Lake

Databricks Jobs/Workflows

Experience developing batch or incremental ETL/ELT pipelines.

Experience with one or more ETL technologies such as Informatica PowerCenter, AWS Glue, SSIS or similar.

Experience working with relational databases and SQL-based data processing.

Understanding of data transformation, source-to-target mapping and ETL development.

Experience with unit testing, data validation and troubleshooting.

Basic understanding of Bronze/Silver/Gold or other layered data architectures.

Ability to work within an established development framework and follow coding standards.

Good analytical, problem-solving and communication skills.

Bachelor's degree in Computer Science, Information Technology, Engineering or equivalent experience.

Nice to Have

Databricks certification.

Experience with Lakeflow Declarative Pipelines / Delta Live Tables.

Experience with Unity Catalog.

Experience with Databricks Asset Bundles and CI/CD.

Experience with AWS S3, Glue and Redshift.

Experience with Auto Loader or streaming ingestion.

Experience with CDC and SCD Type 1 / Type 2 processing.

Experience with data quality, audit and error-handling frameworks.

Experience with Informatica PowerCenter mappings/workflows.

Experience with AWS services including S3, Glue, Lambda and Redshift.

Experience with Spark/Delta performance optimization.

Experience working in a cloud data modernization or migration project.

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com, @nttdatafed.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit