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Senior Data Platform Engineer

London, Greater London, United Kingdom

Live, first seen by us 28 days ago
Pay
Pay not listed
Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting
Employment
Contract — employment source
Employment type in the employer’s posting: Contractor
From the employer’s posting

What you’ll work on

Full posting
  • Build batch and streaming pipelines with Dataflow, Dataproc, Pub/Sub and Cloud Composer

  • Architect data lake, warehouse and lakehouse solutions, including BigQuery modeling and tuning

  • Provision data infrastructure with Terraform and CI/CD pipelines

  • Implement data governance, lineage, quality and cataloging frameworks for regulatory needs

  • Apply security controls such as IAM, encryption, KMS, data masking and access controls

From the employer’s posting
Develop and optimize batch and streaming data pipelines using services such as Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
Architect data lake, data warehouse, and lakehouse solutions, including data modeling and performance tuning in BigQuery.
Provision and manage data infrastructure using Terraform and CI/CD pipelines.
Implement data governance, lineage, quality, and cataloging frameworks to meet regulatory and client requirements.
Apply security best practices across data environments, including IAM, encryption, KMS, data masking, and access controls.

What you’ll bring

All qualifications

Core experience

  • 7+ years of experience in data engineering or data platform engineering, with at least 3 years in a senior or lead capacity.
  • Experience in banking, insurance, or other regulated financial services environments.
  • Proficiency in Python and SQL, with experience in Spark or Apache Beam.
  • Experience with data governance and quality tools such as Dataplex, Data Catalog, dbt, or Great Expectations.
  • Experience designing data warehouse and data lake architectures, including data modeling.
  • Experience with containerization and orchestration (Docker, Kubernetes/GKE).
Qualification wording
7+ years of experience in data engineering or data platform engineering, with at least 3 years in a senior or lead capacity.
Experience in banking, insurance, or other regulated financial services environments.
Proficiency in Python and SQL, with experience in Spark or Apache Beam.
Experience with data governance and quality tools such as Dataplex, Data Catalog, dbt, or Great Expectations.
Experience designing data warehouse and data lake architectures, including data modeling.
Experience with containerization and orchestration (Docker, Kubernetes/GKE).
Apply at Bits In Glass

Posting record

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Status in our records
Live
First seen by us
Oct 7, 202628 days ago
Recorded sightings
28
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 28

Similar jobs usually come down between day 5 and day 54.

From 10,704 similar postings that came down. Coming down is not always a hire.

Bits In Glass is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • BigQuery
  • Databricks
  • dbt
  • Docker
  • GCP
  • Kafka
  • Kubernetes
  • Snowflake
  • Spark
  • Terraform
  • Airflow
Where the posting names them
- Working experience with GCP data services such as BigQuery, Dataflow, Dataproc, Cloud Composer (Airflow), Pub/Sub, Cloud Storage, Bigtable, and Cloud SQL. - Proficiency in Python and SQL, with experience in Spark or Apache Beam. - Experience designing data warehouse and data lake architectures, including data modeling.
- Strong hands-on experience building and operating data platforms on GCP. - Working experience with GCP data services such as BigQuery, Dataflow, Dataproc, Cloud Composer (Airflow), Pub/Sub, Cloud Storage, Bigtable, and Cloud SQL. - Proficiency in Python and SQL, with experience in Spark or Apache Beam.
- Develop and optimize batch and streaming data pipelines using services such as Dataflow, Dataproc, Pub/Sub, and Cloud Composer. - Architect data lake, data warehouse, and lakehouse solutions, including data modeling and performance tuning in BigQuery. - Provision and manage data infrastructure using Terraform and CI/CD pipelines.
- Experience with containerization and orchestration (Docker, Kubernetes/GKE). - Exposure to other data platforms such as Snowflake, Databricks, or Kafka. - Experience supporting AI/ML workloads or Vertex AI pipelines.
- Experience in banking, insurance, or other regulated financial services environments. - Experience with data governance and quality tools such as Dataplex, Data Catalog, dbt, or Great Expectations. - Experience with containerization and orchestration (Docker, Kubernetes/GKE).
- Experience with data governance and quality tools such as Dataplex, Data Catalog, dbt, or Great Expectations. - Experience with containerization and orchestration (Docker, Kubernetes/GKE). - Exposure to other data platforms such as Snowflake, Databricks, or Kafka.
Honoured internationally as a Great Place to Work and recipient of various partner achievement awards, BIG emphasizes team collaboration, technological innovation, and tangible client outcomes. Our staff consists of skilled engineering professionals dedicated to tackling difficult technical problems, driving joint success, and guiding enterprise organizations through digital transformation with certainty. Bits In Glass UK is seeking a Senior Data Platform Engineer to design, build and operate secure, scalable data platforms on Google Cloud for financial sector clients. Working closely with client teams, architects and internal stakeholders, you will deliver batch and streaming pipelines, modern data warehouse and lakehouse solutions, and robust governance and security controls using infrastructure-as-code and DataOps practices. This opportunity suits an experienced GCP data engineer with a strong security mindset, who enjoys solving complex data challenges, mentoring others, and communicating clearly with both technical and non-technical audiences.
Roles and Responsibilities - Design, build, and maintain scalable data platforms on Google Cloud Platform for financial sector clients. - Develop and optimize batch and streaming data pipelines using services such as Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
Nice to Have - GCP Professional Data Engineer or Professional Cloud Architect certification. - Experience in banking, insurance, or other regulated financial services environments.
- Architect data lake, data warehouse, and lakehouse solutions, including data modeling and performance tuning in BigQuery. - Provision and manage data infrastructure using Terraform and CI/CD pipelines. - Implement data governance, lineage, quality, and cataloging frameworks to meet regulatory and client requirements.
- Experience designing data warehouse and data lake architectures, including data modeling. - Working experience with Terraform and CI/CD tooling such as Jenkins, GitHub, or Cloud Build. - Strong understanding of data security in regulated environments.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Bits In Glass (BIG) operates as a rapidly expanding AI and automation consultancy, maintaining presence throughout Canada, the United States, India, and Great Britain. The firm's technical scope encompasses over ten primary platforms across artificial intelligence, cloud infrastructure, data management, automation solutions, and enterprise software.


Honoured internationally as a Great Place to Work and recipient of various partner achievement awards, BIG emphasizes team collaboration, technological innovation, and tangible client outcomes. Our staff consists of skilled engineering professionals dedicated to tackling difficult technical problems, driving joint success, and guiding enterprise organizations through digital transformation with certainty.


Bits In Glass UK is seeking a Senior Data Platform Engineer to design, build and operate secure, scalable data platforms on Google Cloud for financial sector clients. Working closely with client teams, architects and internal stakeholders, you will deliver batch and streaming pipelines, modern data warehouse and lakehouse solutions, and robust governance and security controls using infrastructure-as-code and DataOps practices.


This opportunity suits an experienced GCP data engineer with a strong security mindset, who enjoys solving complex data challenges, mentoring others, and communicating clearly with both technical and non-technical audiences.


Roles and Responsibilities

  • Design, build, and maintain scalable data platforms on Google Cloud Platform for financial sector clients.
  • Develop and optimize batch and streaming data pipelines using services such as Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
  • Architect data lake, data warehouse, and lakehouse solutions, including data modeling and performance tuning in BigQuery.
  • Provision and manage data infrastructure using Terraform and CI/CD pipelines.
  • Implement data governance, lineage, quality, and cataloging frameworks to meet regulatory and client requirements.
  • Apply security best practices across data environments, including IAM, encryption, KMS, data masking, and access controls.
  • Monitor, troubleshoot, and resolve platform performance, reliability, and data quality issues.
  • Collaborate with client teams, architects, and internal stakeholders to translate business needs into technical solutions.
  • Mentor engineers, contribute to technical standards, and promote DataOps and engineering best practices across the team.
  • Communicate architecture decisions, progress, and analysis clearly to technical and non-technical audiences.


Required Skills

  • 7+ years of experience in data engineering or data platform engineering, with at least 3 years in a senior or lead capacity.
  • Strong hands-on experience building and operating data platforms on GCP.
  • Working experience with GCP data services such as BigQuery, Dataflow, Dataproc, Cloud Composer (Airflow), Pub/Sub, Cloud Storage, Bigtable, and Cloud SQL.
  • Proficiency in Python and SQL, with experience in Spark or Apache Beam.
  • Experience designing data warehouse and data lake architectures, including data modeling.
  • Working experience with Terraform and CI/CD tooling such as Jenkins, GitHub, or Cloud Build.
  • Strong understanding of data security in regulated environments.
  • Strong knowledge of DevOps/DataOps and Agile delivery practices.
  • Excellent written and verbal communication skills.
  • Strong analytical, debugging, and problem-solving skills.


Nice to Have

  • GCP Professional Data Engineer or Professional Cloud Architect certification.
  • Experience in banking, insurance, or other regulated financial services environments.
  • Experience with data governance and quality tools such as Dataplex, Data Catalog, dbt, or Great Expectations.
  • Experience with containerization and orchestration (Docker, Kubernetes/GKE).
  • Exposure to other data platforms such as Snowflake, Databricks, or Kafka.
  • Experience supporting AI/ML workloads or Vertex AI pipelines.


Bits In Glass (BIG) operates as a rapidly expanding AI and automation consultancy, maintaining presence throughout Canada, the United States, India, and Great Britain. The firm's technical scope encompasses over ten primary platforms across artificial intelligence, cloud infrastructure, data management, automation solutions, and enterprise software. Our staff consists of skilled engineering professionals dedicated to tackling difficult technical problems, driving joint success, and guiding enterprise organizations through digital transformation with certainty.

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London, Greater London, United Kingdom

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