Description

You will build and maintain the technical infrastructure for ETL processes across diverse data sources. You optimize data availability through APIs, shared services, and cloud-based processing, storage, and analytics solutions.

Responsibilities

• Build technical infrastructure for Extraction, Transformation, and Loading (ETL) using Python and other scripting languages.
• Perform SQL tuning, data integration, and complex technical analysis for multiple divisional projects.
• Execute risk assessments and system tests to ensure data processing security and functional integrity.
• Align data engineering activities with enterprise architecture strategies and provide technical guidance on database cybersecurity.

Required Skills

• 6+ years of experience in Data Engineering.
• Expertise in SQL, PL/SQL, and writing sophisticated stored procedures.
• Proficiency in Python (object-oriented programming) and shell scripting.
• Extensive experience with DB2, Snowflake, Oracle, MongoDB, Redshift, and PostgreSQL.
• Hands-on experience with ETL and streaming tools, including Kafka, AdeptiA, or Alteryx.
• Experience managing large datasets using S3, Splunk, YugabyteDB, or Aerospike.
• Knowledge of machine learning libraries including Pandas, NumPy, Scikit-learn, and TensorFlow.
• Ability to integrate and consume APIs for data parsing and analytics.
• Understanding of hybrid on-prem and cloud data architectures and event-based systems.

Preferred Skills

• Experience with Agile methodologies such as Kanban and SCRUM.
• Familiarity with quantitative techniques, statistics, and time series data analysis.

Key Skills

Education

Any Graduate