Data Engineer: Cloud Data Pipelines for Public Sector

Different Technologies Pty Ltd.; Greater London; Hybrid; GBP 70,000 - 100,000; Full time

Benefits offered by this job

25 days annual leave

Private health insurance

Training budget

5% pension

Employee referral programme

Gym discounts

Job summary

Daintta is a growing data engineering consultancy partnering with government clients to deliver data-driven insights. You will develop pipelines for analytics, ML and business intelligence in a security-conscious environment.

The role requires 3+ years in data engineering, strong experience with Spark, Python, Kafka, SQL and Airflow, and a willingness to work hybrid in London or Cheltenham. You will contribute to client engagements and growth of the company.

Qualifications

• 3+ years of degree-level industry experience in data engineering
• Experience in client delivery across projects involving data analysis, ETL/ELT, data intelligence and data security
• Experience with cloud-based infrastructure (AWS, Azure, GCP) and data engineering tools
• Demonstrable data quality checks, data warehousing schemas and CI/CD in pipelines
• Ability to work in a security-conscious environment and understand data privacy requirements

Responsibilities

• Assess clients' technical needs and manage stakeholders
• Identify data sources and design ETL/ELT concepts
• Design on-premise, cloud, and hybrid data engineering solutions
• Model, structure and store data for analytics, ML, BI and compliance
• Ingest structured and unstructured data from diverse formats
• Ensure data security, storage compliance and data governance
• Support client engagements, pitches and company strategy

Skills

Client delivery

ETL/ELT

Data pipelines

Security clearance

CI/CD tooling

Education

Degree in data engineering or related field

Tools

Spark

Python

Kafka

SQL

Airflow

PostgreSQL

Elasticsearch

Job description

Daintta is a growing data engineering consultancy partnering with government clients to deliver data-driven insights. You will develop pipelines for analytics, ML and business intelligence in a security-conscious environment.

The role requires 3+ years in data engineering, strong experience with Spark, Python, Kafka, SQL and Airflow, and a willingness to work hybrid in London or Cheltenham. You will contribute to client engagements and growth of the company.