Senior Data Engineer

Who you are

• 10+ years of meaningful experience in big data and analytics
• Bachelor’s / master’s degree or equivalent experience in computer science engineering, or a related field
• Strong programming skills in languages such as Python, Java, or Scala
• Hands-on experience with Databricks, SQL, and data modelling
• Proficiency with big data tools (e.g., Apache Spark, Apache Kafka, Presto, etc.) and cloud services (e.g., Azure, AWS, GCP)
• Familiarity with data visualization tools and business intelligence (e.g., Power BI)
• Solid grasp of ETL workflows within databases / warehouses such as Oracle, PostgreSQL, SQL Server etc
• Excellent problem-solving and interpersonal skills
• Experience with machine learning frameworks and tools such as Azure ML Studio, AWS Sagemaker etc
• Knowledge of real-time data processing and stream analytics such as Apache Kafka, Azure Event Hubs or similar
• Hands on experience with real-time analytical databases such as Clickhouse or Apache Druid/Pinot or similar

What the job involves

• We are seeking a highly skilled and innovative Senior Data Engineer to join our team
• In this role, you will be responsible for designing, building, and managing our data infrastructure and analytics solutions to enable data-driven decision-making across the organization
• You will work on complex datasets and collaborate with cross-functional teams to unlock insights and deliver actionable intelligence
• Design, develop, and optimize big data pipelines, architectures, and data integration workflows
• Build scalable and efficient data storage solutions, such as data lakes, warehouses, or cloud-based systems
• Collaborate with data scientists, analysts, and stakeholders to understand data requirements and deliver solutions
• Develop and maintain ETL processes for ingesting, transforming, and loading data from diverse sources
• Conduct advanced data analysis, modelling, and visualization to identify patterns and insights
• Ensure data quality, reliability, and security across systems
• Work with distributed computing frameworks (e.g., Spark, Hive, Hadoop) to process and analyse large datasets
• Stay up to date with the latest trends and technologies in big data, analytics, and cloud platforms