Data Engineer

Repointing Execution & Delivery

• Lead script-level repointing across 593 downstream scripts (PySpark, BTEQ, Shell, SQL, IICS, SSIS) and 154 Databricks MLOps scripts from Teradata/SQL Server/Minio to Snowflake.
• Execute SQL syntax conversion for Teradata BTEQ scripts to Snowflake-compatible SQL, leveraging utility frameworks provided by the SI Partner (Infosys).
• Drive Airflow variable and connection updates across all migrated workflows, ensuring pipelines point to Snowflake endpoints post-cutover.
• Manage the script modification and change management process, coordinating production-to-parallel sync within the required 1-business-day SLA.
• Own the deployment and sign-off process for each migration wave, maintaining runbooks and go/no-go checklists per domain group.
• Manage data copy requests for Minio-related assets and coordinate initial load and incremental sync activities with the SI Partner.

Team Leadership

• Lead and coordinate a team of 6-8 Data Engineer I and Data Engineer II resources (onshore and offshore) across parallel migration workstreams.
• Assign scripts per complexity band (S/M/L) to team members, track daily progress against the LOE estimates, and escalate blockers promptly.
• Review code changes, validate SQL conversion quality, and enforce engineering standards before submission to EBI team for review.
• Mentor junior engineers on Snowflake-specific constructs (virtual warehouses, stages, Snowpark, streams & tasks) and Teradata-to-Snowflake syntax differences.
• Conduct daily stand-ups and provide weekly migration status reports to the Program Manager and client stakeholders.

Validation, Reconciliation & Quality

• Own the parallel run and reconciliation cycle - execute data validation against Teradata source and Snowflake target, targeting sign-off within 2-3 reconciliation iterations per workflow.
• Drive automation of unit testing and validation frameworks in collaboration with the SI Partner, tracking outcomes in the centralized validation dashboard.
• Triage and root-cause data mismatches, performance gaps, and pipeline failures during the parallel run phase; coordinate resolution with SI Partner support as needed.
• Ensure UAT sign-off from the EBI Data team on each domain group before scheduling production cutover.
• Conduct performance and load testing on migrated Snowflake workloads; incorporate SI Partner guidance on query optimization and warehouse sizing.

Stakeholder & SI Partner Coordination

• Serve as the technical point of contact with the EBI client team for the repointing workstream - attending daily syncs, steering calls, and design reviews.
• Coordinate with Infosys (SI Partner) on alignment of major SQL conversion utilities prior to team execution, ensuring conversion frameworks are available at program kick-off.
• Translate migration risks and data reconciliation issues into clear business-impact language for non-technical stakeholders.
• Maintain shared documentation: migration decision log, runbooks, issue trackers, and lessons learned repository.

Technical Skills (Must Have)

• 8+ years of data engineering experience; minimum 3 years hands-on with Snowflake (architecture, SQL dialect, performance tuning, RBAC).
• Proven experience migrating Teradata workloads to Snowflake - including BTEQ/ANSI SQL translation, macro conversion, and stored procedure migration.
• Strong PySpark and Python skills; experience working with Databricks is required (MLOps pipelines a strong plus).
• Working knowledge of Apache Airflow - DAG management, variable configuration, connection updates across environments.
• Familiarity with IICS (Informatica Intelligent Cloud Services) and/or SSIS (.dtsx) pipelines in a migration context.
• Solid understanding of data lake and object store patterns (Minio, S3, ADLS) and how they integrate with Snowflake external stages.
• Experience with SQL Server, Teradata, and/or Netezza as source platforms is required.
• Strong Git proficiency; experience with CI/CD pipelines and code change coordination across environments (dev ? parallel ? prod).

Delivery & Leadership Skills

• Proven experience leading a team of 5+ engineers in a fast-paced, time-bound migration or repointing program.
• Ability to manage scope across complexity bands (S/M/L scripts) and balance team capacity against tight delivery timelines.
• Strong stakeholder management - able to communicate migration status, risks, and escalation paths clearly to both technical and business audiences.
• Experience working in a client-facing consulting or managed services model is strongly preferred.
• Comfortable coordinating with an SI Partner - understanding scope boundaries, handoff points, and utility dependencies without micromanaging.

PREFERRED BACKGROUND

• Domain experience in US Telecom - CDR processing, subscriber data, network inventory, or revenue assurance datasets aligned to EBI workloads (NRD, Compensation, TechOps, CB, etc.).
• Snowflake SnowPro Core or Advanced Data Engineer certification.
• Prior experience delivering migrations within an company, consulting firm, or analytics-driven managed services engagement.
• Exposure to data observability and reconciliation tooling (Great Expectations, Monte Carlo, or custom validation frameworks).
• Familiarity with Snowflake Snowpark, Streams & Tasks, or Dynamic Tables for replacing legacy Teradata batch patterns.
• Experience with Databricks Unity Catalog or MLOps frameworks in an enterprise telecom context.

WHAT WE'RE LOOKING FOR

A hands-on technical lead who can walk into a live migration program, immediately understand script-level complexity, own execution accountability, and keep a distributed team moving at pace - without needing the SI Partner to hold their hand.

• Someone who can read a Teradata BTEQ script and a Snowflake execution plan in the same breath.
• A communicator who can run a 15-minute daily sync with EBI stakeholders and translate yesterday's reconciliation failures into a clear resolution path.
• A leader who treats the 593-script scope not as a backlog item but as a delivery commitment with a hard October 2026 deadline.
• A professional who understands the rhythm of parallel run validation - tolerates expected data mismatches, drives iterative reconciliation, and knows when to escalate versus resolve.