Desired skills: ·

A university degree from a reputed University with a record of academic excellence in Mathematics, Computer Science, Engineering, Physics, or similar. ·

8+ years of relevant experience in Data Engineering, warehousing, ETL, automation, big data and cloud technologies, etc. ·

Ability to write clean, scalable, maintainable code in Python.

Has a good understanding of software engineering concepts and patterns.

Proficiency in other languages like Scala, Java, C#, C++ are an advantage. ·

Proven record of building and maintaining data pipelines deployed in at least one of the big 3 cloud ML stacks (AWS, Azure, GCP). ·

Hands-on experience with:

o Open-source ETL, and data pipeline and orchestration of such tools as Apache Airflow and Nifi.

o Large Scale/ Big Data technology, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka.

o Fast and distributed data processing in Ray, Dask, DuckDb, Polars, cuDF

o Building performant code in C, C++ and interfaces with python in PyO3.rs, Cython

o Workflow orchestration tools like Apache Airflow.

o Containerisation with Docker, deployment on Kubernetes.

o NoSql and graph databases.

o Unix server administration and shell scripting. ·

Experience in building scalable data pipelines for highly unstructured data. ·

Experience in building DWH and data lakes architectures. ·

Experience in working in cross-functional team with software engineers, data scientists and machine learning engineers. ·

Experience in working with or leading an off-shore team. ·

Proven record of building data science environments deploying ML solutions in at least one of the big 3 cloud ML stacks (Azure/Aws/GCP) and on Kubernetes clusters. ·

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 our international teams