QA Automation Lead

Kalpita Technologies; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Kalpita Technologies is seeking a senior Data Migration Engineer to lead end-to-end data migrations to Azure SQL. You will profile legacy systems, build source-to-target mappings, and design repeatable ETL/ELT pipelines for 10-year data loads.

The role requires strong T-SQL skills, deep SQL Server and Azure SQL experience, and proficiency with ADF/SSIS. You will mentor engineers and collaborate with US client stakeholders on data quality and cutover planning.

Qualifications

• 8–12 years of data engineering experience.
• Experience with end-to-end legacy-to-cloud migrations.
• Deep SQL Server experience and Azure SQL Database expertise.
• Proficient with ETL/ELT tooling: Azure Data Factory and/or SSIS.

Responsibilities

• Own end-to-end migration strategy: extraction, mapping, transformation, loading, reconciliation, cutover.
• Profile and reverse-engineer legacy SQL Server objects with minimal documentation.
• Design repeatable ETL/ELT pipelines for large historical data loads.

Skills

T-SQL

Azure SQL Database

Data Modeling

Python

PowerShell

English Communication

Leadership / Mentoring

CI/CD

JSON & API data formats

Performance Tuning

Education

Microsoft Azure Data Engineer Associate (DP-203) certification

Bachelor's degree or equivalent in a related field

Tools

Azure Data Factory

SSIS

GitHub Actions

Azure DevOps

Terraform

dbt

Databricks

Job description

Role Requirements

• Own the end-to-end migration strategy, including extraction, mapping, transformation, loading, reconciliation, and cutover.
• Profile and reverse-engineer legacy SQL Server databases, views, and materialized view outputs with little or no documentation.
• Build source-to-target mappings from the legacy model into the new operational and reporting databases on Azure SQL.
• Design and build repeatable, idempotent ETL/ELT pipelines for a 10-year historical data load.
• Define data quality rules, cleansing logic, and exception handling for bad, duplicate, and orphaned records.
• Build automated reconciliation using row counts, checksums, aggregates, and record-level comparisons between legacy and target systems.
• Run parallel legacy-versus-platform cycles, including comparison of JSON report outputs, and drive defects to closure.
• Plan and rehearse production cutover, including runbooks, mock migrations, timing, rollback, and sign-off criteria.
• Work with the Solution Architect, Business Analysts, and client SMEs to resolve data rules and business definitions.
• Lead and review the work of a Data Migration Engineer and set coding and testing standards.
• Tune load performance and query performance on large historical datasets.
• Report migration status, risks, and data issues clearly and early to client stakeholders.
• Have 8–12 years of data engineering experience, including at least 2 large legacy-to-cloud migrations delivered end to end as the lead.
• Demonstrate expert T-SQL skills, including complex views, stored procedures, CTEs, window functions, indexing, and query plans.
• Have deep SQL Server experience and hands-on Azure SQL Database experience, including serverless or elastic tiers.
• Have strong ETL/ELT tooling experience with Azure Data Factory and/or SSIS, plus scripting in Python or PowerShell.
• Demonstrate proven data reconciliation and validation practices using automated checks rather than manual spot-checking.
• Have data modeling experience for transactional (OLTP) and reporting workloads.
• Be comfortable reading and producing JSON and comparing structured outputs between systems.
• Have cutover planning experience, including mock runs, rollback plans, and go/no-go criteria.
• Have experience with Git and CI/CD pipelines using GitHub Actions or Azure DevOps for database code and migration jobs.
• Have led or mentored at least 1–2 engineers.
• Demonstrate clear written and spoken English and the ability to work directly with US client stakeholders.
• Survey, assessment, or research data experience, including Qualtrics exports, respondent-level data, and longitudinal datasets, is good to have.
• Education-sector data experience, such as school or district reference data, is preferred.
• Experience with event-driven or microservices architectures and data flows through queues is preferred.
• Experience with Azure Blob Storage, Key Vault, Azure Monitor/Log Analytics, dbt, Databricks, Microsoft Fabric, and infrastructure as code using Terraform or Bicep is good to have.
• Experience with AI coding assistants such as Claude Code or GitHub Copilot is good to have.
• Microsoft Azure Data Engineer Associate (DP-203) certification or equivalent is preferred.