Data Engineer

About the role

SimplifyNext is looking for a Data Engineer to design, build and operate scalable lake‑house platforms for its clients. You will work on modern cloud stacks such as Databricks, Spark, Microsoft Fabric or AWS, collaborating with architects, AI engineers and business analysts to deliver end‑to‑end data solutions.

Key responsibilities

• Design and implement ETL/ELT pipelines on AWS (Glue, Step Functions, Lambda, S3), Databricks, Spark or Microsoft Fabric.
• Build lake‑house solutions using open table formats (Apache Iceberg, Delta Lake, S3 Tables) with schema evolution and ACID transactions.
• Define and maintain automated data‑quality frameworks, monitoring accuracy, completeness and consistency.
• Apply DevOps practices – CI/CD pipelines, infrastructure‑as‑code (Terraform, CloudFormation) – for repeatable deployments.
• Prepare data for AI workloads, supporting feature pipelines and knowledge‑base creation.

Required profile

• Degree in Computer Science, Data Engineering, Information Systems or related field.
• 4+ years of hands‑on data‑engineering experience building production pipelines.
• Experience delivering data projects in regulated or public‑sector environments is a plus.

Required skills

• Databricks, Apache Spark, Microsoft Fabric, AWS (Glue, Step Functions, Lambda, S3, Redshift).
• Open table formats: Apache Iceberg, Delta Lake, S3 Tables.
• SQL and programming in Python, Scala or Java.
• Infrastructure‑as‑code tools: Terraform, CloudFormation.