Dimension Data

2 weeks ago

Senior Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Design and deliver scalable batch and near real-time data pipelines and cloud-native data products for advanced reporting and analytics. Build performant BigQuery data models and optimized SQL transformations, implement Python and PySpark workflows, and ensure data quality through robust modeling and validation. Use GCP services (BigQuery, Dataflow, Cloud Composer, Pub/Sub, GCS) to operate modern platforms, troubleshoot issues, and improve performance with strong engineering practices like CI/CD, code reviews, and testing.

Location: Anywhere

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Design and deliver batch and real-time ETL/ELT pipelines across cloud environments for analytics and reporting.
•Write and optimize advanced SQL transformations and build performant, cost-efficient BigQuery data models.
•Implement scalable data processing solutions with Python and PySpark, ensuring maintainable and high-quality code.
•Build robust data models and apply validation practices to maintain data accuracy and reliability.
•Use GCP services (BigQuery, Dataflow, Cloud Composer, Pub/Sub, GCS) to build and operate modern data platforms, optimizing performance and troubleshooting issues.

Pay and Benefits

Perks:Health InsuranceLearning Budget

Key Requirements

•At least 5 years of experience as a Data Engineer building scalable data pipelines and cloud-based data ecosystems.
•Strong expertise in SQL and hands-on experience building performant datasets in BigQuery (or similar cloud data warehouses).
•Proven experience with Python and PySpark for scalable data processing in distributed environments.
•Solid understanding of data modeling plus ELT/ETL patterns and data quality best practices.
•Experience with Google Cloud Platform, particularly BigQuery, Dataflow, Cloud Composer, GCS, or equivalent cloud data services.

Experience:5+ years

Education:Bachelor's in computer science

Skills:CollaborationEngineering rigorCI/CD awarenessCode reviewTesting standards

Tech Stack:SQLBigQuerySparkPySparkPythonGoogle Cloud PlatformGCPDataflowCloud ComposerPub/SubGCSETLELTCI/CDVersion controlAutomated testingTerraformAnsibleChefShell scripting

Company Brief

Dimension Data

Dimension Data, operating under NTT Ltd, provides managed IT services, cloud and data center solutions, networking, cybersecurity, and digital transformation services to enterprise customers worldwide.

Industry: Professional Services

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Valuation: Public Company (Market Cap in USD)

Headquarters: London, United Kingdom

Founded: 1983

Website LinkedIn

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Dimension Data

2 weeks ago

Senior Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Location: Anywhere

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Design and deliver batch and real-time ETL/ELT pipelines across cloud environments for analytics and reporting.
•Write and optimize advanced SQL transformations and build performant, cost-efficient BigQuery data models.
•Implement scalable data processing solutions with Python and PySpark, ensuring maintainable and high-quality code.
•Build robust data models and apply validation practices to maintain data accuracy and reliability.
•Use GCP services (BigQuery, Dataflow, Cloud Composer, Pub/Sub, GCS) to build and operate modern data platforms, optimizing performance and troubleshooting issues.

Pay and Benefits

Perks:Health InsuranceLearning Budget

Key Requirements

•At least 5 years of experience as a Data Engineer building scalable data pipelines and cloud-based data ecosystems.
•Strong expertise in SQL and hands-on experience building performant datasets in BigQuery (or similar cloud data warehouses).
•Proven experience with Python and PySpark for scalable data processing in distributed environments.
•Solid understanding of data modeling plus ELT/ETL patterns and data quality best practices.
•Experience with Google Cloud Platform, particularly BigQuery, Dataflow, Cloud Composer, GCS, or equivalent cloud data services.

Experience:5+ years

Education:Bachelor's in computer science

Skills:CollaborationEngineering rigorCI/CD awarenessCode reviewTesting standards

Tech Stack:SQLBigQuerySparkPySparkPythonGoogle Cloud PlatformGCPDataflowCloud ComposerPub/SubGCSETLELTCI/CDVersion controlAutomated testingTerraformAnsibleChefShell scripting

Company Brief

Dimension Data

Industry: Professional Services

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Valuation: Public Company (Market Cap in USD)

Headquarters: London, United Kingdom

Founded: 1983

Website LinkedIn