
Senior Data Architect
6 days ago
Project description
Join our Development Center and become a member of our open-minded, progressive and professional team. You will have a chance to grow your technical and soft skills, and build a thorough expertise of the industry of our client. In this role you will be working on projects for one our world famous clients, a large international investment bank.
We are seeking a technically strong and hands-on Data Architect to design and own end-to-end data sourcing and integration solutions. This role focuses on architecting scalable, secure, and efficient data pipelines that ingest, process, and publish data from a wide variety of sources—including traditional databases, Hadoop, NoSQL systems, and file-based inputs—into our hybrid data platform spanning Google Cloud and on-premises infrastructure.
This is a hands-on role, requiring active participation in solution implementation, including code commits, technical reviews, and close collaboration with engineering teams.
On top of attractive salary and benefits package, Luxoft will invest into your professional training, and allow you to grow your professional career.
Responsibilities
Key Responsibilities:
Solution Architecture
Design comprehensive data sourcing strategies and technical interfaces with feed providers.
Architect data pipelines for ingestion, transformation, and delivery to distribution layers such as BigQuery and Cloud Storage.
Ensure alignment with enterprise data governance, security, and performance standards.
Platform Integration
Define integration patterns for hybrid environments (GCP + on-prem).
Own the technical blueprint for data movement, preprocessing, and publication.
Stakeholder Collaboration
Engage with internal and external data providers to agree on technical specifications and delivery formats.
Collaborate with engineering teams to ensure architectural designs are implemented effectively.
Technical Execution
Contribute directly to codebases and configuration repositories.
Participate in code reviews, testing, and deployment processes.
Skills
Must have
Required Skills & Experience:
Deep expertise in:
Oracle, Postgres, Hadoop, NoSQL databases
Data pipeline frameworks (e.g., Apache Spark, Airflow, Dataflow, Dataproc)
Google Cloud Platform (BigQuery, Cloud Storage, Pub/Sub, Composer, CloudRun, IAM)
Data virtualization tools such as Trino (Presto, or Denodo, or similar)
Cloud security and IAM (Identity and Access Management) best practices
Strong understanding of hybrid cloud architectures and data lifecycle management.
Experience designing scalable and secure data solutions in enterprise environments.
Excellent communication and stakeholder engagement skills.
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