Senior Data Platform Engineer
London, Greater London, United Kingdom
- 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 postingBuild 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 qualificationsCore 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).
Tools in this posting
- Python
- SQL
- BigQuery
- Databricks
- dbt
- Docker
- GCP
- Kafka
- Kubernetes
- Snowflake
- Spark
- Terraform
- Airflow
Source — Tool mentions in context
- 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.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 7, 2026 · 22 days ago
- Recorded sightings
- 21
- Last seen by us
- Oct 28, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on bitsinglassca.bamboohr.com. The employer’s form will show what is required.
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Job description
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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- Location & working pattern
London, Greater London, United Kingdom
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