Description

Responsibilities

• Design, build, and support ETL pipelines for extracting data from multiple Jira source repositories.
• Ingest Jira data from APIs, database extracts, CSV/JSON/XML files, or other approved source formats.
• Transform and normalize Jira entities such as projects, issues, epics, stories, tasks, subtasks, users, comments, attachments, workflows, statuses, priorities, labels, custom fields, links, and history.
• Implement deduplication logic across multiple Jira repositories to identify duplicate issues, users, components, labels, and related metadata.
• Support data mapping from source Jira schemas into the target Jira configuration.
• Load cleansed and validated data into a staging Jira repository and support final migration into the target Jira instance.
• Archive source repository data into Snowflake using structured, queryable data models.
• Build reusable ETL scripts, jobs, and data quality checks.
• Collaborate with data analysts, QA testers, Jira administrators, and customer stakeholders.
• Document ETL logic, transformation rules, exception handling, reconciliation results, and load procedures.
• Troubleshoot data load failures, schema mismatches, encoding issues, API limitations, and data quality exceptions.
• ETL design documents.
• Source-to-target mapping specifications.
• Transformation and deduplication logic.
• Snowflake archival data model.
• ETL jobs/scripts/pipelines.
• Data reconciliation reports.
• Load execution logs and exception reports.
• Migration support documentation.

Skills Must have

• Strong ETL development experience using tools such as Python, SQL, Snowflake, Informatica, Talend, Matillion, dbt, Airflow, Azure Data Factory, or similar platforms.
• Strong SQL skills for profiling, transformation, reconciliation, and validation.
• Experience working with Snowflake for data storage, archival, reporting, and analytical queries.
• Experience with Jira data structures, Jira APIs, Jira exports, or similar enterprise ticketing/work management platforms.
• Experience with data normalization, deduplication, merge rules, survivorship logic, and master-data-style matching.
• Strong understanding of batch data processing, error handling, logging, and restartability.
• Ability to work with semi-structured data formats such as JSON, XML, and CSV.
• Experience handling large data volumes and complex source-to-target mappings.

Nice to have

• Experience with Jira Cloud, Jira Data Center, or Jira Service Management migrations.
• Experience using Atlassian REST APIs.
• Experience with Python libraries such as pandas, requests, SQLAlchemy, PySpark, or Snowpark.
• Experience with data governance, lineage, auditability, and archival strategies.
• Experience with Azure, AWS, or cloud-based data platforms.
• Familiarity with Agile delivery, sprint planning, and migration cutover activities

Key Skills

Education

Bachelor's degree