Galytix - Lead Data Engineer - Data Warehousing/ETL

1 month ago


Gurugram, India Galytix Full time

Job Description :


Lead Data engineer helps to architect, design, implement, and optimise our data ingestion, transformation pipelines and processes. He or she develops data models, processing pipelines, and back-end services supporting the data science teams, automates processes, builds integrations, and builds analytics.

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).

- 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.


Hands-on experience with :


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


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


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


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


- Workflow orchestration tools like Apache Airflow.


- Containerisation with Docker, deployment on Kubernetes.


- NoSql and graph databases


- Unix server administration and shell scripting.

(ref:hirist.tech)

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