Lead Data Engineer

What is the project, and why should you care?

We are looking for a highly skilled Lead Data Engineer to join our team. In this role, you will lead data initiatives across multiple projects, guide junior team members, and contribute to the design and implementation of modern data architectures in cloud environments. You’ll also support pre-sales activities and help shape data strategies for various clients.

You will be an excellent fit for this position if you have:

• Deep understanding of Data Warehousing (DWH) concepts and best practices.
• Hands-on experience building data warehouses and data lakes in cloud environments (AWS, GCP, Azure).
• Strong proficiency in Python for data engineering and automation.
• Excellent SQL skills, including experience with performance tuning and large-scale datasets.
• Familiarity with modern data orchestration tools (e.g., Airflow, dbt, Prefect).
• Experience with distributed data processing frameworks (e.g., Spark, Dask) and cloud-native data warehouses (e.g., BigQuery, Redshift, Snowflake).
• Knowledge of CI/CD and infrastructure-as-code tools (e.g., Terraform, CloudFormation).
• Strong communication skills and ability to translate business needs into technical solutions.
• Proven ability to lead teams and manage multiple priorities in a fast-paced environment.
• Upper-intermediate or higher level of English, both written and spoken, is required for collaboration, documentation, and client interaction.

Nice to Have:

• Knowledge or experience in the iGaming industry.
• Exposure to AI/ML workflows and production integration.
• Experience with real-time/streaming data technologies (e.g., Kafka, Flink, Kinesis).
• Familiarity with BI and visualization tools (e.g., Looker, Power BI, Tableau).

Here are some of the things you’ll be working on:

• Provide hands-on technical leadership and mentorship to junior and mid-level data engineers.
• Work part-time across multiple concurrent data engineering projects.
• Design and implement scalable data architectures and pipelines in cloud platforms (e.g., AWS, GCP, Azure).
• Participate in pre-sales activities such as technical discovery, solution design, and proposal development.
• Collaborate with stakeholders (data scientists, analysts, business teams) to gather requirements and deliver high-impact data solutions.
• Develop, optimize, and maintain ETL/ELT pipelines for structured and unstructured data.
• Ensure best practices for data quality, security, and governance are followed.
• Integrate and evaluate third-party tools and platforms as needed.
• Contribute to internal documentation, process improvements, and knowledge sharing.