Description

You will manage end-to-end data lifecycles, from building scalable pipelines to delivering actionable business insights.

Responsibilities

• Develop and maintain ETL processes to integrate data from databases, APIs, and third-party platforms.
• Build and optimize data pipelines for performance, scalability, and reliability.
• Design and develop data models to support business intelligence and machine learning applications.
• Create interactive dashboards and visualizations in Tableau or Power BI to communicate KPIs.
• Ensure data quality by identifying and correcting inconsistencies across all data sources.
• Collaborate with data scientists and stakeholders to translate business problems into data-driven solutions.

Required Skills

• 10+ years of total professional experience.
• Proficiency in Python, R, or Scala for data processing and analysis.
• Strong experience with Apache Spark, Apache Airflow, and Kafka.
• Expertise in SQL and working with large-scale relational and NoSQL databases.
• Hands-on experience with distributed computing frameworks like Hadoop and Spark.
• Experience building pipelines using ETL tools or custom Python scripts.
• Proficiency with Git for version control.
• Knowledge of data modeling, schema design, and data cleansing techniques.
• Experience with cloud data platforms such as AWS, Azure, or GCP.

Preferred Skills

• Experience with statistical analysis, machine learning, and predictive modeling.
• Familiarity with DevOps practices and CI/CD for data pipelines.
• Exposure to data privacy and security regulations like GDPR and CCPA.

Key Skills

Education

Bachelor's degree