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Lead Data Engineer (Romania / Ukraine)

Remote:

Full Remote

Contract:

Full time

Salary:

84 - 90K yearly

Experience:

Senior (5-10 years)

Work from:

Ukraine, Romania

Offer summary

Qualifications:

5-7 years of data engineering experience, Proficiency in Python and SQL, Experience with Databricks and ETL processes, Knowledge of AWS or GCP cloud platforms, Familiarity with visualization tools like Sisense.

Key responsabilities:

Design scalable data lake and pipelines
Drive system design and inter-team alignment
Work across ETL, warehousing, and cloud systems
Define data management and governance best practices
Mentor engineers and communicate strategies to stakeholders

AmorServ Information Technology & Services Startup https://linktr.ee/

11 - 50 Employees

See more AmorServ offers

Job description

Role: Lead Data Engineer

Location: Romania, Ukraine (Remote)

Years of Experience: 5-7 years

Pay: $84,000 - $90,000 PA

Required Skill: Python, SQL,Databricks, Snowflake, ETL, AWS, GCP, Airbyte, Postgres, Kafka, Sisense, CircleCI, Grafana, Kubernetes (EKS)

Language Required: English C1 Level

Job Description

This role emphasizes creating robust, scalable, and secure data lake, ingestion, and distribution systems. As a key leader, you will work across the data stack and collaborate with cross-functional teams, setting high standards in data governance, quality, and security.

Key Responsibilities

Data Lake and Pipelines: Design and implement features for ingestion, enrichment, and transformation, ensuring availability, reliability, and scalability.
System Design and Project Alignment: Drive system design, creating alignment and feasibility for projects across teams.
Full Data Stack: Work across ETL processes, data warehousing, visualization, and cloud infrastructure.
Data Management and Governance: Define and implement best practices to ensure data quality, security, and consistency.
Optimization: Develop and optimize Spark jobs, notebooks, and pipelines in Databricks.
Collaboration and Mentorship: Partner with the Chief Architect, mentor engineers, and support DataOps culture.
Stakeholder Communication: Communicate data strategies and plans to stakeholders across the organization.

Required Skills and Experience

Data Engineering: 5+ years in data pipeline design and implementation using Databricks and Python (or PySpark).
SQL & Visualization: Proficiency in SQL and visualization tools such as Sisense or Power BI.
Cloud Platforms: Experience with AWS or GCP, focusing on cloud-native data engineering.
ETL and Data Governance: Expertise in ETL processes and data governance principles to maintain quality and consistency.

Must-Have:

Python, SQL, Databricks, ETL processes
AWS or GCP
Visualization tools (Sisense or similar)
Airbyte or comparable ETL tools
Terraform for environment templating, CI/CD tools (CircleCI, GitHub Actions

Nice to Have:

Kedro, Kafka, and data mesh design
Postgres, Terraform, CircleCI, Grafana
Knowledge of microservices and data modeling

Additional Skills

Technical: Designing large-scale data systems, SQL/NoSQL databases, and familiarity with streaming services like Kafka.
Soft Skills: Strong client-facing abilities, strategic planning, and stakeholder management.

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