Key Skills

Job Description

We are looking for a Data Engineer to design, develop, maintain, and optimize data pipelines and data platforms that support analytics, reporting, and business decision-making. Responsibilities Develop and maintain ETL/ELT pipelines and data integrations. Build and maintain data models, data warehouses, and reporting datasets. Monitor and improve data quality, reliability, and pipeline performance. Troubleshoot and resolve production data issues within agreed SLAs. Optimize data warehouse and cloud platform performance. Collaborate with Data, Analytics, Engineering, Product, Architecture, and Business teams. Document processes, solutions, and data workflows. Requirements Experience as a Data Engineer or similar role. Strong SQL skills and experience with Python and/or PySpark. Experience with ETL/ELT development and data integration. Experience with cloud platforms such as Azure, AWS, or GCP. Experience with data warehouses, databases, or data lakes. Experience with Git/GitHub or Azure DevOps. Strong troubleshooting and problem-solving skills Nice to Have Experience with: Databricks / Apache Spark Azure Data Factory Airflow / dbt Snowflake / Synapse / Azure SQL Production support and incident management. What You'll Do You will play a key role in ensuring reliable, high-quality, and timely data delivery, while contributing to new integrations, platform improvements, and business reporting initiatives.

Core Responsibilities

Develop, maintain, and optimize data pipelines, integrations, data models, warehouses, and reporting datasets. Ensure reliable, high-quality data delivery by monitoring performance and quality, resolving production issues, improving platforms, and collaborating across teams.

Requirements

Candidates should have experience as a Data Engineer or in a similar role, strong SQL skills, and experience with Python and/or PySpark, ETL/ELT, data integration, cloud platforms, and data storage platforms. Git or Azure DevOps experience and strong troubleshooting skills are required; experience with Databricks, Spark, Azure Data Factory, Airflow, dbt, Snowflake, Synapse, Azure SQL, or production support is advantageous.