Data Engineering - Build and maintain data ingestion and transformation. Use Python, SQL, and DBT to deliver scalable, fault-tolerant data flows. Exposure todata warehouse design, Splunk/Dynatrace monitoring, and cloud-native data mesh architectures.

2. Cloud Experience - Experience on Cloud Native design Data Architectures especially on GCP and Hands-on experience on GCP services like GCS, BigQuery, Cloud Composer, PubSub,CloudSQL, Dataflow & DataProc. Additional experience on other cloud platforms can be considered.

3. Source & API Attribute Mapping - Map UI fields and business attributes to source system APIs (batch or real-time). Covers BIAN entity/attribute mapping, request/response analysis, and end-to-enddata lineage from source to target.

4. Data Quality & Validation - Design and implement automated checks, reconciliation, and validation rules across pipelines and datasets. Ensure completeness, accuracy, and fitness-for-purposeof all data delivered.

5. Stakeholder Workshops & Facilitation - Plan and run workshops with business, technology, and downstream teams to capture data requirements, validate sourcing, and align on scope. Communicateclearly with both technical and non-technical audiences.

6. Agile Delivery -Work within cross-functional Agile squads alongside BAs, engineers, SMEs, and risk partners. Manage priorities, contribute to sprint planning, and drive outcomes iteratively.

7.



Documentation & Data Dictionary - Produce clear, structured documentation including data dictionaries, source-to-target mappings, data models, and API specs — written for both technical andbusiness audiences.

8. Strong Communication & Collaboration - Tailor messaging for different audiences, tell a explicit story with data, and work effectively across cross-functional teams — balancing technical depthwith business clarity.

9. Analytical Thinking & Problem Solving - Apply critical thinking to diagnose data issues, resolve pipeline or quality problems, and translate complex findings into actionable insights forstakeholders.

GOOD TO HAVE — ADVANTAGEOUS

10. BI Dashboards & Reporting - Design and build self-service dashboards using Power BI, Qlik Sense, or Tableau. Automate reporting to provide stakeholders with accurate, timely performanceand compliance metrics.

11. BIAN Knowledge - Familiarity with the BIAN (Banking Industry Architecture Network) reference model — including Service Domain structures, BQ interaction models, and entity/attribute conventions.

12. Banking Experience - Prior experience in banking, financial services, or consulting. Non-Financial Risk frameworks.

Pay: ₹1,800,000.00 - ₹3,600,000.00 per year

Work Location: Hybrid remote in Bengaluru, Karnataka (Bengaluru, Bengaluru Urban District)

📌 Senior Data Engineer (Bengaluru)
🏢 Ananta Services
📍 Bengaluru