[Hiring] Senior Analytics Data Engineer @MWDN

Role Description

Join a forward-thinking consulting environment that helps companies scale through modern cloud, data, and AI-driven solutions. The team partners with organizations across industries to design and implement robust, multi-cloud architectures, combining deep infrastructure expertise with advanced data platforms.

• Lead implementation of end-to-end data platforms across the cloud pipeline and analytics/transformation layers.
• Build and optimize data ingestion pipelines - batch and streaming - using modern orchestration tools.
• Design and implement data transformation logic and semantic data models using dbt or equivalent.
• Evaluate and recommend data stack components across the full delivery lifecycle, contributing to the team's stack selection mandate.
• Participate in client-facing technical sessions, sprint reviews, and architecture working groups alongside the Senior Data Architect & Advisor.
• Provide engineering leadership and code review for the three internal mid-level engineers.
• Implement infrastructure-as-code practices to ensure consistent cloud deployments.
• Build and maintain data marts, aggregated layers, and reporting-ready datasets aligned to project requirements.
• Document data lineage, transformation logic, and pipeline architecture consistently and clearly.

Qualifications

• 7+ years in data engineering, analytics engineering, or cloud data platform roles - with demonstrable breadth across both pipeline and analytics layers.
• Hands-on multi-cloud experience across at least two of AWS, Azure, GCP and their native data services.
• Experienced with usage/oversight of generated code via AI.
• Strong Python proficiency for pipeline development and automation.
• Hands-on experience with dbt (Core or Cloud) or equivalent transformation frameworks.
• Experience with orchestration tools (Airflow, Prefect, Dagster, or equivalent).
• Familiarity with streaming platforms (Kafka, Kinesis, Pub/Sub, or equivalent).
• Strong SQL proficiency and experience with cloud data warehouses (Snowflake, BigQuery, Redshift, Synapse).
• Understanding of data modeling patterns - star schema, data vault, and/or lakehouse.
• Comfortable presenting technical content to non-technical client stakeholders.

Requirements

• Experience with lakehouse platforms (Databricks, Apache Iceberg, Delta Lake).
• Infrastructure-as-code experience (Terraform or equivalent).
• Exposure to BI tooling and semantic layer design (Looker, Power BI, Tableau, or equivalent).
• Fintech or regulated industry background.
• Prior experience in a consultancy or client-delivery environment.

Benefits

• People-first management with minimal bureaucracy.
• A friendly company culture, proven by employees who choose to return.
• Flexible working hours.
• 29 days of PTO (18 working days per year plus all national holidays).
• 10 paid sick days.
• Full financial and legal support for independent contractors.
• Free English classes, with native speakers or Ukrainian teachers.
• Dedicated HR support.