Senior Data Platform Engineer
Key Skills for This Role
Full Job Posting
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.
Qualifications
- 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.
About Bits In Glass
Designs and implements automated software systems for large enterprises.
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