Data Engineer (Databricks)

Syntax Consultancy Ltd; Leeds; Hybrid; GBP 83,000 - 120,000; Full time

Job summary

Syntax Consultancy Ltd. is seeking a hands-on Data Engineer (Databricks) for a 6‑month contract in Leeds with hybrid work. You will run and maintain production data pipelines on Databricks and AWS, ensuring reliability and timely incident resolution.

The role covers L2/L3 production support and data engineering tasks, focusing on Spark SQL, Delta Lake, Parquet and Hive metastore integration, with emphasis on security via IAM/KMS. Start ASAP in October 2026.

Qualifications

• Hands-on Databricks, PySpark, AWS, SQL and Python experience.
• Experience with Spark SQL, Delta Lake, Parquet and Hive metastore tables including schemas and partitions.
• Experience with AWS services (S3, IAM, CloudWatch) and data access security.
• Owning incidents from investigation through recovery and root-cause analysis with remediation.
• Familiarity with Git, code reviews, CI/CD and controlled production deployments.

Responsibilities

• Run and maintain production data pipelines on Databricks and AWS.
• Keep data processing reliable, resolve incidents and improve performance.
• Provide incident updates, escalations and timely remediation.
• Diagnose issues in Python, PySpark, SQL and Databricks jobs and AWS integrations.
• Support CI/CD and production deployment processes with testing and rollback.

Skills

Databricks

PySpark

AWS

SQL

Python

Spark UI

CI/CD

Git

Linux

Terraform

Tools

Hive Metastore

Delta Lake

Parquet

CloudWatch

KMS

Job description

Data Engineer (Databricks)

Leeds (Hybrid)

6 Month Contract

£(Apply online only)/day (Inside IR35)

Hybrid Working Model - primarily working from home with travel to the Leeds office 1-2 days per month.

Start ASAP in October 2026.

Data Engineer needed with strong hands‑on Databricks, PySpark, AWS, SQL + Python experience.

A chance to work with a leading global IT transformation on a large‑scale Government project:

• Hands‑on Data Engineer to run + maintain production data pipelines on Databricks and AWS.
• Keeping scheduled data processing reliable, resolve incidents, fixes + improving data services performance.
• The role combines L2/L3 production support and Data Engineering tasks.
• Databricks experience covering notebooks, scheduled jobs, cluster configuration, driver / executor logs, Spark UI + performance troubleshooting.
• Supporting + maintaining production data pipelines, including incident investigation, safe recovery, root cause analysis + permanent remediation.
• Experience of Spark SQL, Delta Lake, Parquet + Hive metastore tables, including schemas, partitions and the relationship between table metadata and underlying files.
• Hands‑on AWS experience, particularly S3, IAM and CloudWatch, with an understanding of role‑based access, KMS encryption and diagnosing data access failures.
• Owning incidents from investigation through recovery and closure. Diagnosing issues in Python, PySpark, SQL, Databricks jobs and AWS integrations + providing clear progress updates and timely escalation.
• Working knowledge of Git, code reviews, CI/CD and controlled production deployments, including testing, rollback and release validation.

Advantageous: AWS Glue, Lambda, Step Functions, Linux, Shell Scripts, Terraform, Gitlab, Jenkins