Torchora
Back to Home

Key Responsibilities and Required Skills for Data Migration Analyst

💰 $ - $

DataITMigrationAnalytics

🎯 Role Definition

A Data Migration Analyst plans, designs, and executes the safe, accurate, and auditable movement of data between systems during application upgrades, cloud migrations, platform consolidations, or mergers and acquisitions. This role is responsible for end-to-end migration lifecycle work: scoping, profiling, mapping, ETL/ELT development, testing, validation, cutover orchestration, reconciliation and post-migration support while ensuring data quality, security and regulatory compliance. The ideal candidate combines strong technical skills (SQL, ETL tools, cloud data services), domain knowledge, and exceptional stakeholder management to deliver repeatable, low-risk migration programs.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Data Analyst or Data Engineer
  • ETL Developer or Integration Developer
  • Business Systems Analyst with data responsibilities

Advancement To:

  • Senior Data Migration Analyst
  • Data Migration Lead / Migration Delivery Manager
  • Data Architect or Data Engineering Manager
  • Master Data Management (MDM) Lead or Data Governance Lead

Lateral Moves:

  • Data Integration Specialist
  • Data Quality Analyst
  • MDM Analyst or Data Governance Analyst

Core Responsibilities

Primary Functions

  • Lead end-to-end data migration projects for enterprise initiatives, including discovery, source-to-target mapping, extraction, transformation, loading (ETL/ELT), reconciliation and production cutover with documented acceptance criteria.
  • Perform detailed data profiling and root-cause analysis of source systems to identify data quality issues, anomalies, schema inconsistencies, and business rules that impact migration scope and design.
  • Design and document comprehensive source-to-target data mapping specifications, business transformation rules, and field-level lineage to ensure transparent, auditable data movement.
  • Develop, configure and optimize migration jobs and ETL pipelines using industry tools (e.g., Informatica PowerCenter, Talend, SSIS, Azure Data Factory, AWS Glue) and frameworks to meet performance, scalability and SLA targets.
  • Build and maintain reusable migration components, parameterized scripts, and templates to reduce risk and accelerate repeatable migration waves across projects.
  • Create and execute robust test plans including unit tests, integration tests, reconciliation tests, dress rehearsals and runbooks to validate data completeness, accuracy and integrity prior to go-live.
  • Design and implement reconciliation and validation processes (row counts, checksum, business rule checks, exception handling) that prove parity between source and target systems.
  • Coordinate detailed cutover planning and orchestration across application owners, infrastructure, DBA, and business stakeholders; lead runbook execution during scheduled migration windows.
  • Implement data masking, encryption and secure transfer methods to protect sensitive data in transit and at rest, ensuring compliance with company policies and regulatory requirements (GDPR, HIPAA, SOC).
  • Manage migration risk through rollback strategies, contingency planning, and controlled staging environments to minimize production impact.
  • Troubleshoot and resolve migration failures, performance bottlenecks, job errors and data reconciliation exceptions, providing root-cause analysis and permanent fixes.
  • Maintain and publish migration status reports, KPI dashboards and executive summaries that highlight progress, risks, issues and mitigation plans.
  • Collaborate with data architects, application teams and business SMEs to interpret business requirements into technical data migration solutions and ensure alignment with target data models.
  • Implement metadata capture and maintain data lineage documentation in metadata repositories to support auditability, traceability and governance requirements.
  • Evaluate and recommend migration tools, utilities, and third-party services (including cloud-native options) to drive modernization and cost efficiencies.
  • Perform incremental and delta data capture designs and develop change-data-capture (CDC) patterns for minimal downtime migrations.
  • Lead or participate in data cleansing and enrichment initiatives to remediate known data quality issues prior to migration and reduce post-migration incidents.
  • Author and maintain detailed migration artifacts: runbooks, mapping documents, test cases, reconciliation scripts, cutover guides, and post-migration support documentation.
  • Support integration testing and UAT by preparing test data sets, coordinating test runs, analyzing results and applying corrective transformation rules.
  • Ensure migration activities align with broader data governance, master data management and data stewardship processes; facilitate exceptions and approvals as needed.
  • Mentor junior team members and contractors on migration best practices, tool usage, scripting standards and troubleshooting techniques.
  • Drive continuous improvement by capturing lessons learned after each migration wave and integrating process improvements into future migration planning.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis to help stakeholders understand migration impacts and data behavior.
  • Contribute to the organization's data migration strategy and roadmap, helping standardize processes and toolchains across programs.
  • Collaborate with business units to translate data needs into engineering requirements and prioritize migration scope according to business value and risk.
  • Participate in sprint planning and agile ceremonies within the data engineering team; break down migration work into deliverable user stories and tasks.
  • Provide knowledge transfer and training to operations and support teams for post-migration monitoring and issue resolution.
  • Assist audit and compliance teams by producing migration evidence, reconciliation logs and change documentation during reviews.
  • Engage with vendor support and third-party consultants to accelerate complex migrations and resolve tool-specific issues.
  • Conduct pre- and post-migration performance tuning and capacity planning with DBAs and cloud infrastructure teams.

Required Skills & Competencies

Hard Skills (Technical)

  • Expert SQL: complex joins, window functions, performance tuning, bulk load strategies, and cross-platform SQL dialects.
  • ETL/ELT tools: practical experience with Informatica PowerCenter, Talend, Microsoft SSIS, Azure Data Factory, AWS Glue or similar platforms.
  • Data profiling & quality tools: ability to use profiling utilities and data quality rules to discover and remediate issues (examples: Ataccama, Informatica DQ, Talend DQ).
  • Cloud data platforms: hands-on experience with AWS (S3, RDS, Redshift), Azure (Data Factory, Blob, Synapse), or GCP (BigQuery) and migration patterns to cloud.
  • Scripting and automation: Python, Bash, PowerShell for orchestration, data transformations, validation scripts and automation.
  • Change Data Capture (CDC) and incremental load patterns: knowledge of CDC tooling and strategies for near-zero downtime migrations.
  • Data modeling & metadata management: understanding of canonical models, star/snowflake schemas, and metadata repositories for lineage capture.
  • Data reconciliation & validation: build automated reconciliation processes, checksums, row-level validation and exception handling.
  • API and file-based integrations: parsing JSON/XML, flat-file parsing, FTP/SFTP, and integrating with RESTful services during migrations.
  • Master Data Management and governance awareness: understanding of MDM concepts, business rules and data stewardship responsibilities.
  • Performance tuning & scalability: diagnose ETL bottlenecks, indexing strategies, bulk load best practices and parallelization techniques.
  • Version control and CI/CD: experience using Git, CI pipelines, and automated deployments for migration artifacts.
  • Tools & ticketing: familiarity with JIRA, ServiceNow or equivalent for tracking migration tasks, issues and change requests.

Soft Skills

  • Strong stakeholder management: communicate complex technical status and risks clearly to business and executive audiences.
  • Problem solving and analytical thinking: break down ambiguous requirements and resolve data discrepancies methodically.
  • Attention to detail: meticulous documentation of mappings, transformations and test evidence to support auditability.
  • Project and time management: prioritize concurrent migration tasks and meet strict cutover windows under pressure.
  • Collaboration and teamwork: work closely with cross-functional teams including application owners, DBAs and infrastructure.
  • Adaptability: pivot quickly when scope, timelines or technical constraints change during migration projects.
  • Coaching and knowledge transfer: mentor junior staff and deliver clear runbooks and training sessions.
  • Effective written communication: produce high-quality mapping specs, runbooks, reports and executive summaries.
  • Risk management mindset: proactively identify, quantify and mitigate migration risks and dependencies.
  • Customer focus: align migration outcomes with business priorities and operational readiness requirements.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Information Systems, Data Science, Software Engineering, Business Analytics, or related technical field.

Preferred Education:

  • Master's degree in Data Science, Information Systems, Computer Science or MBA with a strong technical background.
  • Professional certifications in cloud platforms (AWS/Azure/GCP), ETL tools or data governance (e.g., AWS Certified Data Analytics, Microsoft Certified: Azure Data Engineer, Informatica Developer).

Relevant Fields of Study:

  • Computer Science
  • Information Systems
  • Data Science / Analytics
  • Software Engineering
  • Business Analytics

Experience Requirements

Typical Experience Range: 2 – 7 years working with data integration, ETL, or migration projects (enterprise experience preferred)

Preferred:

  • 3–5+ years of direct, hands-on data migration experience with at least one full lifecycle enterprise migration (assessment → design → test → cutover → support).
  • Demonstrated experience with cloud migrations, large-volume data sets, and compliance-sensitive environments.
  • Experience coordinating complex cutovers involving multiple dependent applications and cross-functional stakeholders.
Explore More Careers