Job Description
Day to Day:
In this role, you'll leverage your expertise in GCP and data engineering to modernize legacy applications and build scalable cloud analytics platforms. You'll collaborate with global engineering teams to define and implement enterprise data strategies, working closely with stakeholders to align solutions with business needs and regulatory requirements. Your responsibilities will include designing and delivering a unified data platform on GCP, guiding teams on data modeling and architecture, and advising on best practices for cloud security, DevOps, and data mesh. You'll also support proof-of-concepts, product evaluations, and integration efforts, while enabling insights through AI/ML platforms and modern data solutions.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Skills and Requirements
Must Have:
5+ years of analytics application development experience
5+ years of SQL development experience
Any amount of GCP cloud experience is required
In-depth understanding of cloud architecture and Google Cloud Platform services
Strong understanding of DevOps principles, CI/CD pipelines, and automated testing
Familiarity with cloud security best practices (IAM, encryption, network security)
Experience with domain-driven design and data mesh principles
Ability to design and implement data lakes, warehouses, and analytics platforms
Strong understanding of microservices architecture Plusses:
Bachelor's degree in Computer Science, Engineering, Data Science, or related field
Google Professional Cloud Data Engineer certification
Experience in banking or financial regulatory reporting
Experience migrating legacy analytics applications to cloud platforms
Strong leadership, communication, and presentation skills
Exposure to diverse technologies and platforms
Ability to work in fast-paced, multi-project environments
Strong experience with GCP Big Data tools such as BigQuery, BigTable, Dataflow, Pub/Sub, Data Fusion, Dataproc, Cloud Build, Airflow, and Terraform (or equivalent technologies)
