Bengaluru, Karnataka
Job Summary
We are looking for a sharp, execution-focused Data Engineer to join Salesforce's internal Data Platform team. In this role, you will architect and deliver mission-critical data pipelines that power Informatica's enterprise operations — from financial reporting to Salesforce writeback. You will own complex end-to-end data flows, drive performance at scale, and set the engineering bar for a high-impact team.
Key Responsibilities
Engineering & Delivery
Design and build highly complex Informatica IICS mappings, taskflows, workflows, and API integrations from requirements through production.
Write performance-tuned SQL against Azure SQL DB, snowflake, ADLS Gen 2, and other enterprise data stores to implement business-critical logic.
Orchestrate pipelines via Unix shell scripts; implement scheduling with crontab or equivalent for non-standard intervals.
Lead performance tuning initiatives — identify bottlenecks, reduce runtimes, and harden pipelines for production reliability.
Conduct design reviews and code walkthroughs with senior technical audiences; incorporate feedback and maintain knowledge-base articles.
Platform & Architecture
Scale a complex, multi-system data platform spanning cloud (SFDC, Oracle Cloud) and on-premise data sources.
Apply best practices in DWH architecture, data lake design, and ETL engineering to continuously raise the quality bar.
Uncover and champion better ways to build — introduce tooling, patterns, and automation that multiply team output.
Skill Requirements
Must-Have
5+ years hands-on ETL development with Informatica IICS and IDQ — including deep knowledge of internal architecture.
Expert-level SQL skills across relational and cloud databases (Azure SQL DB, ADLS Gen 2, Snowflake, or equivalent).
Strong Unix/Linux scripting; experience automating pipeline orchestration via shell and cron.
Working knowledge of cloud platforms — Salesforce (SFDC), Oracle Cloud, or equivalent SaaS ecosystems.
Exceptional debugging and triage skills; proven ability to diagnose and resolve production incidents under pressure.
Strong analytical thinking with the ability to break down ambiguous problems into clear, executable solutions.
Other Requirements
Strongly Preferred
3–7 years delivering production ETL/ELT on data lakes, data warehouses, or analytical platforms.
Experience with DBT, Snowflake, Jupyter Notebook, Databricks, and Postman for exploratory analysis and API testing.
Familiarity with Python for data engineering, automation, or lightweight analytics.
Track record of leading teams through re-platform or technology modernization efforts.
Knowledge of agile project planning methodologies; experience working directly with Scrum teams.
Nice to Have
Exposure to data science, machine learning, or advanced analytics tooling.
Experience building or consuming REST APIs in data pipeline contexts.
Informatica certifications or participation in Informatica community / partner programs.
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