Senior/Lead Data Engineer

emagine Polska; Warszawa; Hybrid; PLN 180,000 - 240,000; Full time

Job summary

emagine Polska seeks senior/lead data engineers to design and implement end-to-end data architectures and modern data platforms. You will lead ingestion, modeling, storage, and orchestration, driving performance, cost efficiency, and reliability across cloud-native solutions including Microsoft technologies.

You will mentor mid/senior engineers, translate complex decisions for stakeholders, and contribute to long-term platform evolution while embracing a hybrid work model with 2 days in the

Qualifications

• Minimum 5 years of experience in data engineering with cloud-native solutions.
• English proficiency at least B2.
• Ability to mentor engineers and drive platform evolution.
• Strong ability to evaluate trade-offs and communicate with stakeholders.
• Experience with DevOps/DataOps and CI/CD.

Responsibilities

• Design end-to-end data architectures and pipelines.
• Lead data ingestion, modelling, storage, and orchestration.
• Improve performance, cost, and reliability of data systems.
• Mentor mid/junior engineers and establish standards.
• Validate data, document lineage, and monitor pipelines.

Skills

Data architecture

Data ingestion

Data modeling

Cloud-native engineering

Microsoft technologies

Azure Data Factory

Azure Synapse

BigQuery

Delta Lake

SQL

Python

Pandas

Spark

CI/CD

Data validation

Data lineage

Documentation

Monitoring

Tools

ORMs/DB access tools

Job description

Required Qualifications to be successful for both roles (Senior/Lead profiles):

• Technical Skills:
• Strong experience in end-to-end data architecture and design, including ingestion, modeling, storage, and orchestration (e.g., Medallion).
• Proficiency in cloud-native engineering, with a focus on Microsoft technologies (Fabric, Azure Data Factory, Synapse) but open to other cloud platforms (AWS, Google Cloud) with comparable tools.
• Hands-on experience with data warehousing and data lake solutions (e.g., BigQuery, Azure Data Lake, Delta Lake, Amazon Redshift).
• Proficiency in programming languages such as Python (with data-related libraries: e.g., Pandas, Boto3), SQL, or Spark.
• Strong knowledge of RDBMS (e.g., Oracle, MS SQL Server) or NoSQL databases (e.g., MongoDB, ElasticSearch, GBQ).
• Experience with DevOps/DataOps practices, including CI/CD pipelines.
• Ability to implement data validation, lineage, documentation, and monitoring at scale.
• Proven ability to optimize pipelines and storage solutions for performance, cost, and reliability.
• Soft Skills:
• Ability to evaluate trade-offs and make clear, defensible technical choices.
• Translate complex engineering decisions into clear, accurate explanations for non-technical stakeholders.
• Uplift and mentor mid/junior engineers, enforce standards, and foster a collaborative technical culture.
• Break down ambiguous, complex problems into clear, actionable steps and drive them to resolution.
• Take responsibility for outcomes, anticipate issues, and drive long‑term platform evolution.
• Experience:
• Minimum 5 years of experience in data engineering, with a focus on cloud-native solutions and data architecture.
• English proficiency should be at least B2 level.

We want to remind you that it is crucial to validate the following points before sharing any candidate:

• Work model: 2 days per week in the office and 3 days at home.