Our client is a software firm delivering a Data Operating System for Financial Institutions globally. They empower influential decision-makers with actionable insights by connecting the right data at the right time with the right knowledge and algorithms. The platform leverages the power of generative artificial intelligence to ingest and structure data regardless of sources, automate manual processes, run advanced analytics and machine learning models, and spread the insights across the organization – in a world’s first fully integrated solution.

Responsibilities:

• Design, implement, and optimize data ingestion, transformation, and spreading pipelines and processes.
• Develop data models and processing pipelines.
• Build and maintain back-end services supporting the data science teams.
• Automate processes and build integrations.
• Develop and maintain scalable data pipelines for highly unstructured data.
• Collaborate with cross-functional teams, including software engineers, data scientists, and machine learning engineers.
• Work with an off-shore team.

Qualifications:

• A university degree from a reputed institution with a record of academic excellence in Mathematics, Computer Science, Engineering, Physics, or similar.
• 3+ years of relevant experience in Data Engineering, warehousing, ETL, automation, big data, and cloud technologies.
• Proficiency in Python (preferably as developer) and a good understanding of software engineering concepts and patterns.
• Hand-on experience with containerization (Docker, Kubernetes).
• Proven experience in building and maintaining data pipelines deployed in at least one of the big 3 cloud ML stacks (AWS, Azure, GCP).
• Hands-on experience with ETL tools (Apache Airflow, Nifi), big data technologies (Hadoop, Spark, Hive, Impala, PrestoDb, Kafka), workflow orchestration (Apache Airflow), NoSQL and graph databases, Unix server administration, and shell scripting.
• Experience in building DWH and data lakes architectures.
• Excellent written and verbal command of English.
• Strong problem-solving, analytical, and quantitative skills.
• A professional attitude and service orientation with the ability to work with international teams.