About the Role:

We are seeking a skilled and experienced Data Engineer to join our team. In this role, you will be responsible for designing, building, and maintaining robust data pipelines and infrastructure to support our business intelligence and data science initiatives. You will work closely with data scientists, analysts, and business stakeholders to understand their data needs and deliver reliable, scalable, and efficient data solutions.

Key Measures of Performance:

The performance of this role holder will be assessed on the basis of the achievements made on:

The performance of this role holder will be assessed based on the achievements made on:

• Critical data pipelines are robust, observable, and cost-optimised.
• Stakeholders trust the data and can make decisions quickly with minimal manual intervention.
• Junior engineers are mentored effectively, raising the technical bar of the whole team.
• The data platform evolves to handle growing scale and complexity without sacrificing performance

Key Responsibilities:

• Architect & Lead: Design and implement scalable data architectures, including data lakes, warehouses, and streaming solutions.
• End-to-End Ownership: Own pipelines from ingestion to serving layers, ensuring reliability, observability, and cost-efficiency.
• Data Modeling: Define and maintain robust data models to support analytics, machine learning, and operational reporting.
• Mentorship & Leadership: Guide junior and mid-level engineers through code reviews, design discussions, and best practices.
• Performance Optimization: Identify bottlenecks, tune pipelines, and improve query performance at scale.
• Governance & Security: Implement and enforce data quality checks, access control, and compliance with privacy regulations (GDPR, CCPA).
• Collaboration: Work closely with product, engineering, and business stakeholders to translate requirements into scalable data solutions.
• Innovation: Evaluate and introduce new technologies and tools to improve the data platform’s reliability and developer experience.

Requirements

• Experience: 5+ years in data engineering or backend engineering, with a track record of leading large-scale data projects.
• Programming Expertise: Advanced skills in Python (or Scala/Java) and strong proficiency in SQL.
• Big Data Frameworks: Deep experience with Spark, Flink, Beam, or similar distributed data processing engines.
• ETL/ELT Orchestration: Expertise with Airflow, dbt, Dagster, or similar tools.
• Cloud Platforms: Strong experience with at least one major cloud provider (AWS, GCP, Azure) — including data services like Snowflake, BigQuery, Redshift, Databricks.
• Data Modeling: Skilled at designing data schemas (OLTP, OLAP, dimensional models).
• Streaming Data: Experience with Kafka, Kinesis, or Pub/Sub for real-time pipelines.
• DevOps Mindset: Familiarity with CI/CD, infrastructure-as-code (Terraform, CloudFormation), and monitoring/alerting.

• Architect & Lead: Design and implement scalable data architectures, including data lakes, warehouses, and streaming solutions.
• End-to-End Ownership: Own pipelines from ingestion to serving layers, ensuring reliability, observability, and cost-efficiency.
• Data Modeling: Define and maintain robust data models to support analytics, machine learning, and operational reporting.
• Mentorship & Leadership: Guide junior and mid-level engineers through code reviews, design discussions, and best practices.
• Performance Optimization: Identify bottlenecks, tune pipelines, and improve query performance at scale.
• Governance & Security: Implement and enforce data quality checks, access control, and compliance with privacy regulations (GDPR, CCPA).
• Collaboration: Work closely with product, engineering, and business stakeholders to translate requirements into scalable data solutions.
• Innovation: Evaluate and introduce new technologies and tools to improve the data platform’s reliability and developer experience.

• Python (or Scala/Java)
• SQL
• Spark, Flink, Beam
• Airflow, dbt, Dagster
• AWS, GCP, Azure
• Snowflake, BigQuery, Redshift, Databricks
• Data Modeling (OLTP, OLAP, dimensional models)
• Kafka, Kinesis, Pub/Sub
• CI/CD
• Terraform, CloudFormation
• Monitoring/Alerting

• 5+ years in data engineering or backend engineering
• Track record of leading large-scale data projects
• Advanced skills in Python (or Scala/Java)
• Strong proficiency in SQL
• Deep experience with Spark, Flink, Beam, or similar distributed data processing engines
• Expertise with Airflow, dbt, Dagster, or similar tools
• Strong experience with at least one major cloud provider (AWS, GCP, Azure) — including data services like Snowflake, BigQuery, Redshift, Databricks
• Skilled at designing data schemas (OLTP, OLAP, dimensional models)
• Experience with Kafka, Kinesis, or Pub/Sub for real-time pipelines
• Familiarity with CI/CD, infrastructure-as-code (Terraform, CloudFormation), and monitoring/alerting