PRIMARY REQUIREMENTS — MUST HAVE
1. 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-end data 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-purpose of 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. Communicate clearly 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 and business audiences.
8. Strong Communication & Collaboration - Tailor messaging for different audiences, tell a clear story with data, and work effectively across cross-functional teams — balancing technical depth with 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 for stakeholders.
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 performance and compliance metrics.
🌟 Opportunity to work on modern enterprise applications with a collaborative and innovative team.
1. 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-end data 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-purpose of 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. Communicate clearly 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 and business audiences.
8. Strong Communication & Collaboration - Tailor messaging for different audiences, tell a clear story with data, and work effectively across cross-functional teams — balancing technical depth with 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 for stakeholders.
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 performance and compliance metrics.
🌟 Opportunity to work on modern enterprise applications with a collaborative and innovative team.