Data Architect
CSG
AWSPostgres
ML Data Engineer
Smart Working
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇮🇳 India
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudDynamoDBETLGoogle Cloud PlatformNoSQLNumpyPandasPostgresPythonScikit-Learn
About the role
- Run hypothesis-led analysis over large datasets to uncover trends, drivers of outcomes, and craft client-ready narratives.
- Build and maintain industry benchmark datasets that power reports/dashboards; keep definitions and versioning tight.
- Deliver clear, actionable Power BI reports for clients and internal stakeholders; maintain selected stand-alone reports in 3rd-party tools where required.
- Own performance dashboards, operational processes, model version control/registry, and experiment tracking.
- Monitor drift and bias, plan/validate improvements, and manage safe deploy/rollback.
- Keep the feature store fresh from published calls; ensure training data lineage and reproducibility.
- Partner on productised evaluations (automated tests, acceptance thresholds) and bias mitigation aligned to policy.
- Specify, design, and implement dashboards & reports within the KAI solution; integrate with portal and API surfaces.
- Collaborate with platform/DB teams on robust data integration & storage patterns across PostgreSQL/NoSQL and data lake assets.
- Support Copilot auto-report creation where suitable, ensuring source-of-truth metrics and governance.
- Run client-specific studies to test hypotheses and meet project goals; present findings to non-technical audiences.
Requirements
- 5+ years — Python (pandas, NumPy, scikit-learn).
- 4+ years — Databases & LLM familiarity: PostgreSQL and DynamoDB (or equivalent), familiarity with LLM concepts and evaluation methods.
- 4+ years — Power BI & Excel stack: Power BI (data models, DAX), Power Query (M), and advanced Excel (pivots, complex formulas); other BI suites acceptable only with strong Excel experience.
- 4+ years — Data warehousing & ETL.
- 3+ years — Cloud data services & ML Ops tooling: exposure to AWS/Azure and ML Ops tools (feature store, experiment tracker, model registry, monitoring); GCP experience may be considered as a substitute.
- Working style — Self-sufficient; ideally has led self-contained aspects of a project.
Benefits
- Fixed Shifts: 12:00 PM - 9:30 PM IST (Summer) | 1:00 PM - 10:30 PM IST (Winter).
- No Weekend Work: Real work-life balance, not just words.
- Day 1 Benefits: Laptop and full medical insurance provided.
- Support That Matters: Mentorship, community, and forums where ideas are shared.
- True Belonging: A long-term career where your contributions are valued.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonpandasNumPyscikit-learnPostgreSQLDynamoDBPower BIDAXPower QueryETL
Soft skills
self-sufficientcollaborationcommunicationpresentationanalytical thinkingproblem-solvingnarrative craftingclient engagementproject managementhypothesis testing
