Senior Data Engineer (with Cloud experience)

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. 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 Design: Architect data pipelines down to the low-level elements, ensuring clarity and precision in implementation.
• Data Sourcing: Extract data from diverse repositories including relational databases (Oracle, PostgreSQL), NoSQL stores, file systems, and other structured/unstructured sources.
• Data Transformation: Design and implement ETL/ELT workflows to standardize and cleanse data using best practices in data engineering.
• Pipeline Development: Build scalable, fault-tolerant data pipelines that support batch and streaming use cases.
• Cloud data processing: Load transformed data into GCP destinations such as BigQuery or Cloud Storage using tools like Dataproc, Dataflow, and other GCPnative services.
• Workflow Orchestration: Design and manage workflows using orchestration tools such as Apache Airflow or Cloud Composer.
• Data Format Expertise: Work with various data formats including JSON, AVRO, Parquet, CSV, and others.
• Optimization & Monitoring: Ensure performance, reliability, and cost-efficiency of data pipelines through continuous monitoring and tuning.
• Collaboration: Work closely with data architects, analysts, and business stakeholders to understand data requirements and deliver high-quality solutions.

SKILLS

Must have

• Required Skills & Experience:
• Proven experience in data engineering across hybrid environments (on-premise and cloud).
• Strong proficiency in SQL and Python or Java/Scala.
• Hands-on experience with ETL/ELT tools and frameworks.
• Deep understanding of Cloud data services (ideally GCP: BigQuery, Dataproc, Dataflow, Cloud Storage)
• Familiarity with data modeling, schema design, and metadata management.
• Experience with workflow orchestration tools (e.g., Apache Airflow, Cloud Composer).
• Knowledge of data governance, security, and compliance best practices.

Nice to have

Preferred Qualifications: • GCP certification (e.g., Professional Data Engineer) is a major plus • Experience with CI/CD for data pipelines. • Exposure to containerization and Kubernetes. • Familiarity with data cataloging tools / metadata management • Experience with Big Data technologies