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naukri

Data Engineer Consultant

Total-TECH Co
Jeddah, KSA
Senior
1 months ago
Google Cloud PlatformBigQueryDataflowCloud ComposerSQLData Modeling
Free

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Google Cloud PlatformBigQueryDataflow
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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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