Senior Data Engineer

Overview

Key Responsibilities

• Collaborate with Analytics Delivery Leads and Lead Data Engineers to understand business requirements and deliver impactful data solutions
• Work closely with Data Scientists and cross-functional teams to solve complex business problems through data engineering solutions
• Manage data onboarding, data access, and stakeholder coordination for analytics initiatives
• Design, develop, and maintain scalable, secure, and high-performance data pipelines
• Acquire, ingest, process, and transform large-scale structured and unstructured datasets
• Implement data engineering best practices for building reliable and production-ready data platforms
• Perform data wrangling, cleansing, transformation, and feature engineering for machine learning and analytics use cases
• Design and develop modular data pipelines to generate reusable features and modeling datasets
• Build and optimize data architectures supporting advanced analytics and machine learning workloads
• Contribute to data platform design by selecting appropriate technologies across Big Data, SQL, and NoSQL ecosystems
• Ensure data quality, integrity, governance, security, and scalability across the data lifecycle
• Participate in Agile squads and collaborate effectively with stakeholders across business and technology teams
• Contribute to enterprise data architecture strategy and roadmap aligned with business objectives

Core Data Engineering

• Strong experience in Data Engineering and Big Data solutions
• Expert-level proficiency in PySpark
• Strong programming experience in Python
• Experience building large-scale distributed data processing pipelines

Data Processing & ETL

• Data Ingestion
• Data Transformation
• Data Wrangling
• Data Preparation
• Data Modeling
• Feature Engineering
• ETL/ELT Development
• Batch Processing

Database Technologies

• Strong SQL expertise
• Experience with Relational Databases
• Experience with NoSQL Databases

• Google Cloud Data Services

• Databricks
• Hadoop Ecosystem

Machine Learning Data Support

• Feature Engineering for ML Models
• Data Preparation for Analytics and AI Use Cases
• Building Modeling and Feature Tables

• Data Quality Management

• Performance Tuning

• Version Control (Git)

• CI/CD Concepts
• Documentation Standards

Required Soft Skills

• Strong stakeholder management and communication skills
• Experience working with Business Analysts, Data Scientists, and Product Teams
• Ability to translate business requirements into scalable data solutions
• Strong analytical and problem-solving skills
• Experience working in Agile/Scrum environments
• Ability to work independently and within cross-functional teams

Preferred Qualifications

• Experience working in enterprise-scale data platforms
• Experience supporting machine learning and advanced analytics initiatives
• Exposure to cloud-native data engineering solutions
• Experience designing modern data architectures and data lake environments