A high growth environment where you can take new challenges, build a career, make an impact. Cross cultural, multi national exposure, access to experienced leaders and mentors. Competitive compensation and benefits.

Roles & Responsibilities:

Design, develop, and maintain scalable ETL/ELT data pipelines.
Build and manage data lake and data warehouse solutions.
Optimize and automate ingestion, transformation, and delivery of structured and unstructured data.
Implement data quality, lineage, and governance best practices.
Collaborate with Data Science, Visualization, and Engineering teams to operationalize data solutions.
Monitor, debug, and improve data platform performance

Primary Skills:

Advanced Python, Advanced SQL, Relational/Document Databases, Batch and Stream processing, Data pipeline monitoring and management, handling structured and unstructured data, and transformations.
Having basic ML skills is good to have.

Understanding of data modeling, data governance, and CI/CD practices.
Solid experience in debugging and optimizing high-volume data processing.
Hands-on experience with modern data stack Apache Spark, Airflow, dbt, Kafka, or equivalent technologies

Must have:

AWS (or any cloud provider), Hands-on Ubuntu Linux, Bash Shell, Developing with Docker

Secondary Skills:

Communication, a good understanding of project management, and software development workflow.
Experience with containerization (e.g., Docker, Kubernetes) and orchestration (Airflow, Dagster, Cron, etc.).
Familiarity with ML Ops or Data Science workflows.
Knowledge of streaming/batch/on-demand processing data architecture.
Exposure to domain-specific analytics (e.g., retail, healthcare, finance).
Data lake and warehouse technologies (e.g., Databricks, Snowflake, Redshift, BigQuery, Delta Lake).

Why Join Us

Opportunity to work with cutting-edge technologies and innovative projects.
Collaborative and dynamic work environment.
Career growth and professional development opportunities.
Competitive salary and benefits package.

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