At a Glance
- Tasks: Design and build scalable cloud data platforms using AWS, Snowflake, and PySpark.
- Company: Join a leading tech firm recognised for its ethical practices and employee wellbeing.
- Benefits: Enjoy competitive pay, remote work options, and extensive training opportunities.
- Other info: Dynamic hybrid work environment with excellent career growth and wellbeing support.
- Why this job: Make a real impact in data engineering while working with cutting-edge technologies.
- Qualifications: Experience in cloud data engineering and strong skills in SQL and ETL/ELT development.
Cloud Data Engineer
About the Job you are considering:
We are seeking an experienced Cloud Data Engineer with expertise in AWS, Snowflake, dbt, PySpark, and SQL to design, build, and maintain scalable cloud-based data platforms and analytics solutions.
The ideal candidate should have strong experience in cloud data engineering, ETL/ELT development, data transformation, data warehousing, and performance optimization. Experience working in regulated industries such as Banking, Financial Services, Insurance, or Healthcare is preferred.
Hybrid working:
The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
Your Role:
- Design, develop, and maintain scalable data pipelines using AWS cloud services.
- Build and manage ETL/ELT workflows for data ingestion, transformation, validation, and reporting.
- Develop and maintain dbt models, tests, snapshots, macros, and documentation.
- Create high-performance data transformation solutions using PySpark and SQL.
- Design and optimize Snowflake data warehouse solutions.
- Integrate data from multiple sources including databases, APIs, cloud storage, and third‑party systems.
- Implement data quality, reconciliation, audit controls, and exception handling.
- Optimize data processing jobs for performance, scalability, and cost efficiency.
- Develop CI/CD pipelines and automate deployment processes.
- Collaborate with architects, business analysts, QA teams, and stakeholders.
- Ensure data security, governance, compliance, and access controls.
- Support production deployment, monitoring, incident management, and troubleshooting.
- Prepare technical documentation and operational runbooks.
Your Skills
Cloud & Data Engineering
- Strong hands‑on experience with AWS cloud platform.
- Experience in designing cloud‑based data platforms.
- Strong ETL/ELT development experience.
- Experience building enterprise‑grade data pipelines.
Snowflake
- Strong experience with Snowflake Data Warehouse.
- Experience in Snowflake performance tuning.
- Knowledge of Snowpipe, Streams, Tasks, and Stored Procedures.
- Experience implementing RBAC and security controls.
DBT
- Hands‑on experience with dbt Core or dbt Cloud.
- Development of reusable models, macros, tests, and snapshots.
- Data lineage, documentation, and dependency management.
- Integration with CI/CD pipelines.
PySpark & Programming
- Strong PySpark development expertise.
- Experience processing large‑scale datasets.
- Code optimization and performance tuning.
- Data transformation, enrichment, aggregations, and joins.
SQL
- Advanced SQL skills.
- Stored procedures, CTEs, window functions, and query optimization.
- Data warehousing and dimensional modelling concepts.
AWS Skills Expected
Candidate should have experience with one or more of the following AWS services:
- Amazon S3
- AWS Glue
- Amazon EMR
- AWS Lambda
- AWS Step Functions
- Amazon Redshift
- Amazon Athena
- Amazon RDS / Aurora
- AWS IAM
- AWS KMS
- Amazon CloudWatch
- AWS Secrets Manager
Data Modelling Skills
- Star Schema
- Snowflake Schema
- Dimensional Modeling
- Data Vault
- Data Warehouse Design
- Data Lake Architecture
Data Formats
Experience working with:
- Parquet
- Avro
- JSON
- CSV
- ORC
CI/CD & DevOps
- Git
- GitHub
- GitLab
- Bitbucket
- Jenkins
- GitHub Actions
- GitLab CI/CD
- AWS DevOps Tools
Domain Experience (Preferred)
Experience in one or more domains:
- Banking
- Financial Services
- Payments
- Cards
- Loans & Mortgages
- Risk & Compliance
- Regulatory Reporting
- AML
- Fraud Analytics
- Customer Data Platforms
- Financial Reporting
- Data Governance
We are a Disability Confident Employer
The company is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who declare a disability and meet the minimum essential criteria for the role.
Make It Real (what does it mean for you)
- You’ll be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation.
- To help support wellbeing we have trained "Mental Health Champions" across each of our business areas and invested in wellbeing apps such as Thrive and Peppy.
- You will be empowered to explore, innovate, and progress. You will benefit from the company’s learning for life mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and more.
- You will be joining one of the World’s Most Ethical Companies, as recognised by Ethisphere for 13 consecutive years.
Cloud Data Engineer employer: United States Digital Space LLC
United States Digital Space LLC is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration in the heart of Greater London. With a strong focus on employee well-being and flexible work options, we provide ample opportunities for professional growth and development, making it an ideal environment for those looking to make a meaningful impact in the field of AI-enabled SaaS engineering.
Contact Details:
United States Digital Space LLC Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Cloud Data Engineer
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How to prepare for a job interview at United States Digital Space LLC
✨Brush Up on Your Statistics
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
