Data Engineer (Partime)

We are seeking a highly skilled Data Engineer with a deep understanding of the Financial Services Industry to join our team. The ideal candidate will have a strong foundation in cloud data engineering, data security, and experience building data-driven solutions.. Key responsibilities include:
Developing and implementing automation scripts to set up cloud data environments, including development, staging, and production.
Designing a cloud data warehouse optimized for machine learning and artificial intelligence workloads.
Building data pipelines to migrate data from on-premises relational databases (e.g., Oracle) to a cloud data warehouse, focus on batch methods.
Integrate data pipelines with marketing automation tools and customer data platforms

Preference is to work in the office. If that’s not possible, hybrid work will be considered
Competitive salary
Working time within 3-4 months (depending on the project).
Free parking

Expert in Python and SQL programming.
Proficient in GCP data products including BigQuery, Dataflow (or Apache Beam), Composer (or Airflow), and Looker Studio.
Strong understanding of DataOps principles and hands-on experience building data CI/CD pipelines using GitHub, Cloud Build, and Terraform.
Experience working with Oracle databases.
Proven experience working on Google Cloud Platform (GCP).
Ability to work independently, under pressure, and meet project deadlines.
Priority:
Knowledge of Customer Data Platforms (CDPs), marketing automation tools, and experience with Google Analytics and Google Ads.
Experience in infrastructure and networking, data security, data masking, and data encryption.
Business domain knowledge: FSI
Experience in Machine Learning (ML), Artificial Intelligence (AI), and MLOps.