Senior Data Engineer – Contractor

This is a fully remote position, open to applicants in Romania.

📋 Description

• Design and sustain data pipelines for the ingestion, transformation, and export of information across various sources and destinations.

• Develop and enhance scalable data architectures to fulfill business and performance demands.

• Collaborate with analysts and data scientists to provide curated, analysis-ready datasets and facilitate self-service analytics.

• Apply best practices for data quality, testing, monitoring, lineage, and reliability.

• Optimize workflows for improved performance, cost-efficiency, and scalability (e.g., tuning Spark jobs, optimizing queries, implementing partitioning strategies).

• Guarantee secure data handling and compliance with applicable data protection regulations and internal policies.

• Contribute to the documentation, standards, and ongoing enhancement of the data platform and engineering processes.

• Ensure secure and compliant management of data and models, including access controls, auditability, and governance practices.

• Construct and maintain MLOps automation: CI/CD for machine learning, environment management, artifact handling, and versioning of data/models/code.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, or a relevant technical field (or equivalent practical experience).

• Over 6 years of experience as a Data Engineer, responsible for building and maintaining production-grade pipelines and datasets.

• Proficient in Python and SQL, with a strong understanding of data structures, performance, and optimization techniques.

• Practical experience with orchestration tools (such as Airflow, Dagster, Databricks Workflows) and distributed processing in a cloud environment.

• Knowledge of analytical data modeling (including star and snowflake schemas), data warehousing, ETL/ELT patterns, and dimensional concepts.

• Proven experience in constructing reliable incremental data ingestion pipelines from databases and APIs.

• Familiarity with at least one leading cloud provider (GCP, AWS, Azure) and deploying data solutions within the cloud.

• Understanding of CI/CD for data pipelines, Infrastructure as Code (Terraform), and/or DataOps methodologies.

• Strong troubleshooting skills: ability to diagnose issues across data, infrastructure, pipelines, and deployments.

• Collaborative attitude with clear communication skills among engineering, analytics, and business stakeholders.

• Nice to have / big advantage:

• Extensive experience with GCP and its ecosystem: BigQuery, Composer, Dataproc, Cloud Run, Dataplex, Cloud Storage.

• Familiarity with data governance concepts: access control, retention, data classification, auditability, and compliance standards.

• Experience in building observability for data systems (metrics, alerting, data quality checks, incident response).

• Knowledge of model monitoring concepts: drift, data quality issues, performance degradation, bias checks, and alerting strategies.

🏝️ Benefits

• Competitive compensation package.

• myPOS Academy for skill enhancement and training opportunities.

• Unlimited access to courses on LinkedIn Learning.

• Referral bonus for bringing friends into the team, as we believe working with friends is enjoyable.

• Team-building activities, social events, and networking opportunities on a multinational scale.