Senior Data Engineer

Accelerate your development and exposure to high‑performance data platforms and cloud infrastructure. Join Sedona Digital, a fast‑growing scale‑up with the ambition to be recognised as one of the leading technology companies in Romania.

Our global client base needs builders, engineers who enjoy designing and implementing scalable data platforms, have deep expertise in cloud data technologies, and take pride in delivering reliable, well‑governed solutions.

At Sedona, we

• Obsess about our customers

• Build robust, scalable technical solutions

• Create an open, collaborative culture

• Invest in learning and long‑term careers

We are looking for a Senior Data Engineer with strong experience in AWS-based data platforms, Snowflake, data integration, and end-to-end pipeline development. The ideal candidate is comfortable working independently, making sound technical decisions, taking ownership of client data processes, and supporting the delivery of modern data and AI solutions.

The role combines cloud data engineering with responsibility for established data-processing workflows, including a large-scale SAS-based healthcare claims process. The successful candidate will contribute across AWS, Snowflake, data modelling, automation, analytics, and AI initiatives while helping improve the reliability and maintainability of existing solutions.

Responsibilities

• Design, build, and maintain scalable data pipelines and integration workflows using AWS, Snowflake, SQL, and Python.

• Manage data ingestion from APIs, databases, SFTP locations, and file-based sources.

• Build and optimise data models, transformations, and data-quality controls.

• Take ownership of recurring client processes, including the monthly SAS-based claims workflow.

• Monitor and troubleshoot pipelines, batch processes, and production data environments.

• Apply security, governance, access-control, and credential-management best practices.

• Improve pipeline resilience through effective monitoring, error handling, restartability, and recovery.

• Optimise data workloads for performance, scalability, and cost.

• Develop reusable components and patterns for ingestion, transformation, validation, and monitoring.

• Prepare governed and trusted datasets for analytics, reporting, AI, and machine-learning use cases.

• Collaborate with clients and internal stakeholders to translate business requirements into practical technical solutions.

• Identify opportunities to modernise legacy processes, reduce manual effort, and improve operational efficiency.

• Maintain technical documentation, data lineage, business rules, and operational runbooks.

Requirements

• 5+ years of experience in data engineering, ETL/ELT, or data integration.

• Strong experience with AWS data services, including S3 and RDS.

• Hands-on experience with Snowflake, SQL, and data modelling.

• Proficiency in Python or a similar scripting language.

• Experience building and supporting scalable batch data pipelines.

• Experience integrating APIs, databases, SFTP locations, and file-based sources.

• Strong understanding of data transformation, validation, quality, and governance.

• Experience monitoring, troubleshooting, and optimising production data processes.

• Ability to work independently and take ownership of client-facing deliverables.

• Strong problem-solving, documentation, and communication skills.

• Experience with SAS datasets and data-processing programs.

• Hold a valid Microsoft certification or commit to completing a relevant certification within three months of joining.

Preferred Skills (Nice to Have)

• Experience with Secure FTP / SFTP and Gzip-compressed files.

• Experience processing large, partitioned datasets.

• Knowledge of server-based batch processing.

• Experience with medical-benefit or pharmacy-benefit claims data.

• Familiarity with Databricks, AI, machine learning, or generative AI use cases.

• Understanding of CI/CD, monitoring, and automation practices.

• Experience with Power BI or other analytics and visualisation tools.

• Experience working in regulated or security-sensitive environments.