Senior Data Engineer within Data Team

• Lead the team efforts in maintaining and enhancing the Holding’s data platform based on Greenplum and Dataiku: suggest, design, and implement new components and features, monitor, and increase the platform performance;
• Design, implement and maintain data pipelines for ingesting data from Strategic assets to the Holding’s platform;
• Resolve issues with data pipelines, data availability and quality on the platform;
• Estimate required hardware, financial and people resources for the platform improvement initiatives;
• Together with the data technology, data governance and data science teams at Strategic assets implement various cross-company data & analytics initiatives;
• Help the data technology teams at the Strategic assets to define their annual action plans and evaluate their execution;
• Facilitate the connecting and onboarding of new Strategic assets to the data platform: plan the activities, supervise the execution;
• Organize and facilitate technical knowledge sharing among the Strategic assets;
• With other colleagues from the Holding’s Data office, participate in the overall platform governance processes definition and improvement;
• Participate in annual data office activities planning and budgeting;
• Mentor and develop junior team members, including those outside of direct reports – both within the Holding and at Strategic assets.

Requirements

• Rich experience with data platforms based on various technologies: architecture design, hands-on implementation, track record of large-scale data projects implementation;

• At least 2 years of DWH administration / maintenance experience (ideally, Greenplum / Postgres);
• Min 2 years of team lead experience (at least 2 direct reports);
• At least 3 years of planning, designing, implementing, monitoring and fixing data pipelines in complex environments, and large variability of data sources;
• Strong knowledge of SQL, good Python skills;
• Deep familiarity with modern data management stack: DWH, Data Lakes, Lakehouses, ETL/ELT, MPP databases, orchestration, data cataloguing and quality management tools, containerized execution, etc.;
• Experience of identifying, investigating, and resolving of data pipelines issues, data quality issues, platform performance issues in large data landscape.
• Knowledge and active promotion of good engineering practices around data modelling, data access and code writing;
• Experience with continuous integration practices;
• Ability to write, debug, unit test, and performance test data integration processes;
• Strong problem solving/critical thinking skills;
• Upper-intermediate English is a must, spoken Russian is a plus.