Cloud Ace 4.7 ★

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.
Building data pipelines to migrate data from on-premises relational databases (e.g., Oracle) to a cloud data warehouse, focus on batch methods.
Designing a cloud data warehouse optimized for machine learning and artificial intelligence workloads.
Integrate data pipelines with marketing automation tools and customer data platformsProven experience working on Google Cloud Platform (GCP).
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.
Expert in Python and SQL programming.
Experience working with Oracle databases.
Ability to work independently, under pressure, and meet project deadlines.
Priority:
Business domain knowledge: FSI
Experience in infrastructure and networking, data security, data masking, and data encryption.
Knowledge of Customer Data Platforms (CDPs), marketing automation tools, and experience with Google Analytics and Google Ads.
Experience in Machine Learning (ML), Artificial Intelligence (AI), and MLOps.Working time within 3-4 months (depending on the project).
Competitive salary
Preference is to work in the office. If that's not possible, hybrid work will be considered
Free parking