Senior Data Engineer

Syncron AB; Warszawa; Hybrid; PLN 260,000 - 420,000; Full time

Benefits offered by this job

Impactful work

Innovation-driven culture

Professional growth

Global environment

Hybrid work model

Job summary

EazyStock, a startup within Syncron AB, seeks a Senior Data & AI Engineer to own the data foundation from raw data to ML-powered features. You will design a lakehouse on AWS, implement data contracts, and drive DataOps, governance, and scalable MLOps across the platform.

You will collaborate across teams to ensure high-quality data, reliable pipelines, and production-grade AI tooling, with a hybrid work model and global collaborative environment.

Qualifications

• Experience designing ETL/ELT pipelines and data integrations across heterogeneous sources.
• Data modelling, metadata management, data catalogs and lineage.
• Knowledge of data quality and governance standards with automated validation.
• Experience with data contracts, DataOps, and schema evolution in multi-consumer environments.
• CI/CD for data pipelines and infrastructure as code; containerization (Kubernetes).
• Strong AWS data stack skills and experience with S3, Glue, Athena, IAM, Lambda.
• Proficiency in SQL and PostgreSQL; performance tuning and CDC.
• Strong Python and production-grade Java backend ownership.
• Experience integrating with enterprise BI platforms (e.g., Qlik).
• Data Engineering certifications or equivalent credentials.

Responsibilities

• Design and build a lakehouse on AWS with Iceberg; enable efficient querying.
• Ingest data from operational sources and deliver a governed analytical replica.
• Define data contracts, metadata, catalogs, and data lineage.
• Implement CI/CD and observability for data pipelines and infra.
• Build MLOps pipelines for AI/ML features and governance.

Skills

ETL/ELT pipelines

Data modelling

Data governance

Data contracts

DataOps

CI/CD

DevOps

Kubernetes

AWS data stack

SQL

Python

Java

Qlik integration

Mentoring

Education

Data Engineering Certificate (e.g., AWS/GCP DatEng certification)

Tools

Airflow

dbt

SageMaker

MLflow

Kubeflow

OpenSearch / Vector store

Job description

EazyStock is a “startup” within Syncron, a global market leading company developing solutions for after market service optimization. Whilst Syncron’s client base is made of up of large enterprises (e.g. Manitowoc, Mazda, DTNA and JCB), EazyStock work with small to medium sized companies, helping them to optimize their inventories and achieve high levels of customer satisfaction without having excess capital tied up in redundant inventory.

We at EazyStock are an entrepreneurial and international team operating in Europe, Asia and the USA, developing and selling the best cloud-based inventory optimization software solution on the market. Nevertheless, we know that we can only help SMB’s if they know about EazyStock, and how this best-in-class solution will improve their customer satisfaction, increase their profits and reduce their inventory investment!

About the role

We are looking for a Senior Data & AI Engineer to establish the data foundation of EazyStock — an engineer who owns the whole path from raw operational data to a model or an ML&LLM-powered feature in production.

What would you do?

Lakehouse & Data Platform

• Design and build the EazyStock lakehouse on S3 with Apache Iceberg as the table format, AWS Glue for ETL/ELT and cataloging, and Amazon Athena as the query engine.

• Build reliable data integration and ingestion from operational sources.

• Deliver a governed analytical replica that removes reporting load from production systems.

• Design partitioning, compaction, snapshot and retention strategies; own query performance and cloud cost efficiency.

Data Modelling, Contracts & Governance

• Deliver clean, well-modelled data into Qlik Cloud and into AI/ML consumers.

• Define and operate data quality and data governance standards, with automated validation and meaningful alerting.

• Introduce data contracts, schema evolution discipline and DataOps practices so producers and consumers can evolve independently.

• Establish metadata management, data catalogs and lineage as a first-class part of the platform.

DataOps & Automation

• Build CI/CD for data pipelines, infrastructure and configuration using GitHub, Jenkins and AWS DevOps tooling; treat infrastructure as code.

• Implement observability for pipelines: metrics, logging, failure modes, SLAs and runbooks.

• Design for repeatability and rollback — no manual production surgery.

AI/ML & MLOps

• Build and operate MLOps pipelines on AWS — model packaging, deployment, versioning, monitoring and retraining.

• Support our GenAI initiatives: data curation and indexing for RAG, embedding pipelines, and Amazon OpenSearch as a vector store, with models served through Amazon Bedrock.

• Bring engineering discipline to AI work — evaluation, observability, cost control and security — so that AI features are supportable, not experiments in disguise.

Who you are? / What we expect:

• 6+ years of professional experience spanning data engineering and software engineering, with production systems you owned end to end and still stand behind.

• Strong experience designing ETL/ELT pipelines, data models, and data integrations across heterogeneous sources.

• Strong data modelling skills, and real experience with metadata management, data catalogs and lineage.

• Practical experience with data quality and data governance.

• Experience with data contracts, DataOps practices and schema evolution in a multi-consumer environment.

• Confident with DevOps and CI/CD: Jenkins or equivalent, infrastructure as code, containerization (Kubernetes).

• Deep, practical experience with the AWS data stack — S3, AWS Glue, Amazon Athena, IAM, Lambda — and with the operational side of running workloads in the cloud.

• Hands-on experience with Apache Spark, Apache Iceberg (or a comparable open table format such as Delta Lake / Hudi) — including the operational realities: compaction, partition evolution, snapshot management.

• Strong SQL and strong PostgreSQL — query optimization, indexing, execution plans, replication and CDC.

• Strong Python and solid production Java — you can own a backend service, not just call one.

• Experience integrating with Qlik or another enterprise BI platform.

• Data Engineering Certificate: Google Professional Data Engineer, Microsoft Certified Fabric Data Engineer, AWS Certified Data Engineer, Databricks Certified Data Engineer, Snowflake SnowPro Advanced Data Engineer, or equivalent.

• Proven ability to mentor and upskill engineers who are strong developers but new to data.

The icing on the cake:

• Classical ML familiarity — scikit-learn, XGBoost, pandas.

• A track record of leading a greenfield data platform build or a significant cloud data migration.

• Experience with Airflow, dbt or similar.

• Experience with SageMaker, MLflow, Kubeflow or comparable model lifecycle tooling.

• Working experience with LLM-based systems — RAG, embeddings, vector databases, or LLM APIs in a production or serious prototype context

• Practical experience with MLOps: deploying models to production, versioning, monitoring and retraining — and a willingness to own the model lifecycle, not just the data that feeds it.

• Domain experience in Supply Chain, Inventory, Pricing or Service Fullfilment.

We offer:

• Impactful Work – Your contributions will directly shape the future of EazyStock’s product and deliver measurable value to customers worldwide.

• Innovation-Driven Culture – Join a team that thrives on creativity, collaboration, and cutting-edge technology.

• Professional Growth – Opportunities to lead strategic initiatives, influence product direction, and expand your expertise in AI and SaaS.

• Global Environment – Work with colleagues and customers across multiple countries in a truly international setting.
• Flexibility – A hybrid work model that supports work-life balance.

Unsure if you meet all the job requirements but passionate about the role? Syncron values diversity and welcomes all Candidates, even those with non-traditional backgrounds. We believe in transferable skills and a shared passion for success!