You’ll work closely with engineering, analytics, and product teams to ensure data is accurate, accessible, and efficiently processed across the organization.

Key Responsibilities:

Design, develop, and maintain scalable data pipelines and architectures.
Collect, process, and transform data from multiple sources into structured, usable formats.
Ensure data quality, reliability, and security across all systems.
Work with data analysts and data scientists to optimize data models for analytics and machine learning.
Implement ETL (Extract, Transform, Load) processes and automate workflows.
Monitor and troubleshoot data infrastructure, ensuring minimal downtime and high performance.
Collaborate with cross-functional teams to define data requirements and integrate new data sources.
Maintain comprehensive documentation for data systems and processes.

Requirements:

Proven experience as a Data Engineer, ETL Developer, or similar role.
Strong programming skills in Python, SQL, or Scala.
Experience with data pipeline tools (Airflow, dbt, Luigi, etc.).
Familiarity with big data technologies (Spark, Hadoop, Kafka, etc.).
Hands-on experience with cloud data platforms (AWS, GCP, Azure, Snowflake, or Databricks).
Understanding of data modeling, warehousing, and schema design.
Solid knowledge of database systems (PostgreSQL, MySQL, NoSQL).
Strong analytical and problem-solving skills.

Odiin.

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