Data Engineer - Tech Lead

Location: Romania or Ukraine only, job fully remote
Contract: B2B or CIM - you can choose
Salary: 7000-8500 USD gross
Benefits: PTO - 25 days per year, Summer Fridays - last Friday in June to last Friday in August is a half day, Winter Break - two week company closure over Christmas and New Year, Sick Leave - 10 days per year, Annual company offsite in the UK, Team social events and treats (online and in person) and more.

What you’ll do?

As the Tech Lead of Data Engineering, you’ll be at the forefront of we shape it, store it, and use it. You’ll lead a team of highly skilled and mission-driven engineers, committed to making the internet safer for the next generations.

You’ll work together with the other leads across technology, product, and other departments to identify areas of improvement for the overall approach to data engineering, lay the groundwork to enable AI-driven capabilities in our products, and enable everyone with an easy and accessible path to make data-driven decisions.

Together with our Chief Architect, Infosec, and Legal functions, you’ll ensure the overall data and information architecture is kept safe and secure. You’ll work with your team to refine the roadmap and break it down into deliverables of the highest quality and impact.

As a lead, you’ll champion continuous improvement and always aim to improve the product your team owns and measure your impact with the appropriate tech, product, or delivery metrics.

In this role, you will:

• be accountable for: ○ design and implementation of features and services for our data lake, ingestion and distribution systems, ○ availability and performance of our data lake, ingestion, and distribution systems, ○ design and implementation of ingestion, enrichment, and transformation pipelines.
• Lead system design activities aimed to create clarity, alignment, and ascertain feasibility
• Work across the full stack depending on where you can drive the highest impact: from ETL pipelines to data warehousing to visualizations, as well as testing and cloud infrastructure.
• Use your experience in data management and governance to define and implement best practices across our systems ensuring security, consistency and quality across all of our data.
• Develop and optimize Spark jobs, notebooks, and data pipelines within the Databricks environment
• Work with the Chief Architect and ML engineers to define an information architecture capable of enabling easy implementation of data models and catalogues within the data lake, ensuring data quality, integrity, and optimal performance.
• Train/mentor other engineers inside and outside of the team on Data engineering best practices.
• Frequently review system, delivery, and quality metrics and drive the right initiatives to improve them, ensuring long-term quality, scalability, and maintainability of our systems.
• Set the bar for what good quality data looks like, and use your expert knowledge to train and mentor other engineers to improve data quality.
• Ensure business continuity by keeping the design choices well documented and explained, from raw data analysis to defining and implementing data ingestion/enrichment pipelines to creating data visualizations.
• Champion the DataOps culture, and support data systems in production, including participation in our out-of-hours on-call rotations.
• Clearly communicate our data platform strategy and plans to others in the company.

Important technologies:

• Expert understanding of Data pipeline design and implementation using Databricks, and Python (or Python derivative, like PySpark).
• Expert visualization skills using Sisense and/or other visualization tools.
• Expert with SQL.
• Expert understanding of Data management and/or Data governance (making sure the data is of expected volume, schema, etc.)
• Experience with modern cloud-based Data Engineering on AWS or other cloud platforms.

Nice to have:

• Experience with Kedro on Databricks.
• Experience in designing and implementing Data mesh.
• Exposure to Airbyte reading from multiple different data sources.
• Good understanding of microservices architecture principle.
• If that's you, apply to us! Let's create together!