Data Engineer Consultant
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Key skills for this role
About the Role
The Job Description 1- Enterprise Data Ingestion and Data Engineering: Design and build scalable, reusable ingestion pipelines (realtime and batch) on GCP (GCS, BigQuery, Datafl.
Key Skills for This Role
Responsibilities
- Design and build scalable, reusable ingestion pipelines (real time and batch) on GCP (GCS, BigQuery, Dataflow)
- Develop parameterized pipelines using Google native services and/or Informatica IDMC mappings and taskflows
- Implement CDC patterns, idempotent loads, late arriving data handling, and schema evolution
- Optimize BigQuery ingestion strategies (batch vs. streaming, partitioning, clustering)
- Establish version control, CI/CD, and environment promotion (dev/test/prod)
- Profile source data and analyze data quality and patterns
- Design field level mappings, business rules, joins, aggregations, and derivations
- Implement transformations using BigQuery SQL, Dataflow, or IDMC transformation logic
- Build and parameterize end to end workflows using Cloud Composer (Airflow) and/or IDMC taskflows
- Define job dependencies, schedules, SLAs, and failure handling strategies
- Implement retries, backoff strategies, checkpoints, and restartability
- Integrate monitoring, logging, and alerting using Cloud Monitoring, Cloud Logging, and ChatOps tools
Requirements
- 5+ years of experience as a Data Engineer or ETL Developer
- Strong experience with Google Cloud Platform: BigQuery, GCS, Data Stream, Dataflow, Cloud Composer, IAM, Cloud Monitoring
- Proficiency in SQL (BigQuery optimized) and data modeling for analytics
- Hands on experience building production grade, scalable data pipelines
- Experience with CI/CD, Git based version control, and DevOps practices
- Bachelor's degree in Computer Science, Information Technology, Information Systems, or a related field
- Experience with Informatica Intelligent Data Management Cloud (IDMC) CDI, Mass Ingestion, Taskflows (optional)
Full Job Posting
Enterprise Data Ingestion and Data Engineering
- Design and build scalable, reusable ingestion pipelines (realtime and batch) on GCP (GCS, BigQuery, Dataflow).
- Develop parameterized pipelines using Google native services and/or Informatica IDMC mappings and taskflows.
- Implement CDC patterns, idempotent loads, late arriving data handling, and schema evolution.
- Optimize BigQuery ingestion strategies (batch vs. streaming, partitioning, clustering).
- Establish version control, CI/CD, and environment promotion (dev/test/prod).
- Results: GCP native pipelines (Dataflow, Composer, Cloud Run) and/or IDMC mappings/taskflows; BigQuery schema designs (raw / stage / curated zones with partitioning & clustering); CI/CD pipelines, deployment artifacts, and operational runbooks.
Data Mapping & Transformation Design
- Profile source data and analyze data quality and patterns.
- Design field level mappings, business rules, joins, aggregations, and derivations.
- Implement transformations using BigQuery SQL, Dataflow, or IDMC transformation logic.
- Results: Source to Target Mapping (STM) document; Transformation mappings.
Orchestration, Automation & Reliability Engineering
- Build and parameterize end to end workflows using Cloud Composer (Airflow) and/or IDMC taskflows.
- Define job dependencies, schedules, SLAs, and failure handling strategies.
- Implement retries, backoff strategies, checkpoints, and restartability.
- Integrate monitoring, logging, and alerting using Cloud Monitoring, Cloud Logging, and ChatOps tools.
- Results: Production ready orchestration workflows with environment aware parameters; Scheduling calendar, dependency diagrams, and SLA matrix; Alerting, monitoring dashboards, and operational SOPs.
Data Pipelines Monitoring, Performance & Cost Optimization
- Monitor pipeline health, data freshness, volumes, and anomaly patterns.
- Support and monitor data pipelines during off hours and weekends, troubleshooting and resolving issues to ensure SLA compliance.
- Track and manage SLAs related to runtime, failures, cost, and data latency.
- Optimize BigQuery performance (query refactoring, partition pruning, materialized views).
- Manage and optimize GCP costs (storage lifecycle, slot usage, query optimization, caching).
- Results: Daily/weekly operational and SLA reports; Performance and cost optimization plans with before/after metrics; BigQuery tuning guidelines and data materialization strategy.
Requirements
- 5+ years of experience as a Data Engineer or ETL Developer.
- Strong experience with Google Cloud Platform: BigQuery, GCS, Data Stream, Dataflow, Cloud Composer, IAM, Cloud Monitoring.
- Proficiency in SQL (BigQuery optimized) and data modeling for analytics.
- Hands on experience building production grade, scalable data pipelines.
- Experience with CI/CD, Git based version control, and DevOps practices.
- [Optional] Experience with Informatica Intelligent Data Management Cloud (IDMC) CDI, Mass Ingestion, Taskflows.
- Bachelor's degree in Computer Science, Information Technology, Information Systems, or a related.
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