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Open nowFirst seen 39 hours ago

Senior Data Engineer/Analyst

Boardroom Appointments3,354 open roles

Where
Johannesburg, South Africa
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Your applicationOpen nowSenior Data Engineer/AnalystBoardroom Appointments · Johannesburg, South Africa

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Boardroom Appointments's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 39 hours ago

The posting

Senior Data Engineer/Analyst - 3 Year Contract

Qualifications & Experience:

Must-Have:

  • Bachelors or Masters degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
  • 5+ years of experience in data engineering, analytics, or BI development.
  • Strong proficiency in SQL and Python for data manipulation and transformation.
  • Experience with ETL/ELT processes, data modeling, and data warehousing concepts.
  • Expertise in cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Snowflake, Databricks, Kafka).
  • Familiarity with data visualization tools (Power BI, Tableau, Looker).

Nice-to-Have:

  • Experience with AI/ML model deployment for predictive analytics.
  • Knowledge of DevOps for data (CI/CD, Infrastructure-as-Code).
  • Certifications in AWS Data Analytics, Azure Data Engineer, or Google Cloud Professional Data Engineer.

Responsibilities:

Data Engineering & Architecture:

  • Design, develop, and maintain scalable and efficient ETL pipelines for data ingestion, transformation, and storage.
  • Build and optimize data warehouses, data lakes, and real-time streaming solutions to support business intelligence and analytics needs.
  • Ensure data quality, integrity, and security across all data processing workflows.
  • Collaborate with Data Scientists, Analysts, and Software Engineers to design data models that enable advanced analytics.
  • Implement data governance, cataloging, and lineage tracking to ensure transparency and compliance.

Data Analysis & Business Intelligence:

  • Conduct data exploration, statistical analysis, and trend identification to extract actionable insights.
  • Develop interactive dashboards and reports using BI tools like Power BI, Tableau, or Looker.
  • Work closely with business teams to understand KPIs and performance metrics, translating data into valuable insights.
  • Optimize query performance and database efficiency for large-scale data processing.

Cloud & Big Data Technologies:

  • Design and manage cloud-based data solutions (AWS, Azure, GCP) with services such as AWS Glue, Azure Data Factory, Google BigQuery, Snowflake, and Databricks.
  • Work with big data frameworks like Apache Spark, Hadoop, or Kafka for distributed data processing.
  • Develop automated data pipelines using orchestration tools like Airflow, Prefect, or Luigi.

Collaboration & Leadership:

  • Work cross-functionally with engineering, product, and business teams to define data requirements.
  • Mentor junior team members and provide guidance on best practices in data engineering and analytics.
  • Drive continuous improvement initiatives in data architecture, automation, and AI-driven analytics.
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    The review screen in CV Rocket: how each CV was read, round by round.

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