Data Bricks Migration and Support engineer

Job description

Must Have Technical/Functional Skills

• Successfully executed a data migration or modernization to Data Bricks, preferably IBM Data Stage to Data Bricks on AWS
• Should have Experience in handling Large Migrations to Data Bricks.
• Should have good analytical skills to compare the legacy and modern data platform end to end right from source to target.
• Good understanding of DataBricks implementation of Medallion layer architecture.
• Independently Lead and Managed large Data Bricks migrations.

CI/CD Integration

• Implement version control (e.g., Git) and automated deployment processes for Databricks assets Technical and architectural skills required are below.

Core Data Engineering Languages

• Experience in Advanced SQL for building modular analytics workflows, utilizing advanced Common Table Expressions (CTEs), and writing high-performance queries inside Data Bricks SQL Analytics.
• Experience in Python or Scala to build, optimize, and debug complex data transformation scripts, custom functions, and machine learning pipelines.

Big Data & Architecture Core

• Experience in Apache Spark Ecosystem for understanding cluster execution flow, memory allocation, driver/worker nodes, and handling data frames.
• Experience in Delta Lake Architecture to understand ACID transactions on object storage, data skipping, partition strategies, and automated data compaction.

Databricks Platform Expertise

• Experience in Delta Live Tables (DLT) & Workflows for constructing and orchestrating production-ready, declarative streaming, and batch ETL pipelines.
• Experience in Unity Catalog for setting up data governance, column/row-level access control, and tracking end-to-end data lineage across workspaces.
• Experience in Auto Loader for implementing modern, incremental data ingestion patterns from cloud blob storage into the lakehouse. Code Translation & Refactoring

Pipeline Conversion

• Translate visual DataStage Parallel Jobs and Sequences into Python/PySpark scripts or Data bricks Notebooks

Legacy Refactoring

• Modernize legacy logic rather than applying "lift and shift" anti-patterns; adapt workflows to think in distributed DataFrames rather than DataStage stages.

Logic Mapping

• Map DataStage components—such as Aggregators, Joiners, Transformers, and Sort stages—to equivalent Spark operations Testing & Reconciliation

Validation & Reconciliation

• Build automated reconciliation frameworks to compare row counts, checksums, and aggregate sums between legacy DataStage outputs and new Databricks output

Data Cleansing

• Identify and resolve data type discrepancies, null-handling differences, and encoding issues during the extraction and loadi ng phases Platform Orchestration & Governance

Orchestration

• Replace DataStage sequence jobs with Databricks workflows ( or external orchestrators like Azure Data Factory/Airflow) to schedule and manage dependencies

Data Governance

• Enforce data lineage, security, and cataloging using Unity Catalog to ensure compliance in the new Lakehouse environment. GOOD TO Cloud Infrastructure & CI/CD

Cloud Providers (AWS)

• Understanding underlying cloud object storage , identity access management (IAM), and network security configurations.

DevOps & Bundles

• Familiarity with Databricks Asset Bundles (DABs) and CI/CD tools to automate the deployment of workspaces and pipeline assets. Legacy Assessment & Migration Mechanics

Code Conversion & Translation

• The ability to parse legacy code structures and refactor them into Databricks-native code.

AI-Assisted Migration

Skills in using AI coding assistants and open framework agent tools to analyze application interdependencies, automate schema mapping, and accelerate lift-and-shift workloads

Code Conversion & Translation

• The ability to parse legacy code structures from ETL pipelines, Informatica, data Stage preferred Experience working in Agile teams and understanding of data governance frameworks.

Responsibilities

Support post-migration environment from IBM DataStage to Databricks Incident & Lifecycle Management

CI/CD Deployment

• Support code deployments across Development, Test, and Production environments using Databricks Repos and REST APIs

Monitoring & Alerting

• Set up monitoring via Databricks System Tables and observability tools to catch job failures, data anomalies, or latency spikes early Pipeline Maintenance & Orchestration

Workflow Management

• Transition from DataStage job sequences to native data bricks workflows for scheduling, dependency tracking, and alerts

ETL Refactoring

• Troubleshoot and fix issues in generated PySpark or Spark SQL code that replaced legacy DataStage Transformer or Lookup stages

Streaming & Batch Integration

• Support ongoing data ingestion using data bricks autoloader to process files continuously from cloud storage Performance Tuning & Cost Optimization

Compute Management

• Monitor and configure serverless or classic clusters to prevent over-provisioning

Query Optimization

• Analyze Spark execution plans. Replace inefficient row-by-row processing logic (a common DataStage carryover) with vectorized operations and native Spark functions

Storage Optimization

• Maintain Delta Lake tables by enforcing layout optimization (\(ZORDER\) Data Governance & Security

Access Control

• Implement granular permissions, column-masking, and row-level filters using Data bricks unity catalog to replace DataStage's legacy security p olicies

Data Quality

• Utilize Delta Live Tables (DLT) to build pipelines with built-in, declarative data quality expectations and monitoring

Additional Skills

• Excellent communication Skills
• Ability to collaborate with Legacy and Modernize application teams and stake holders Base Salary Range : $120,000 to $140,000 Per Annum TCS Employee Benefits Summary: Discretionary Annual Incentive.

Comprehensive Medical Coverage

Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support

Maternal & Parental Leaves.

Insurance Options

Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth

Commuter Benefits & Certification & Training Reimbursement.

Time Off

Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance

Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. #LI-SV2 #LI-KUMARAN </div

Qualifications

BACHELOR OF COMPUTER SCIENCE