Roles & Responsibilities
Core Responsibilities
Data Pipeline Development & Optimization
Design, develop, and maintain robust ETL/ELT pipelines using Apache PySpark on GCP services like Dataproc and Cloud Composer.
Ensure data pipelines are scalable, efficient, and reliable to handle large volumes of marketing data.
Data Warehousing & Modeling
Implement and manage data warehousing solutions using BigQuery, ensuring optimal performance and cost-efficiency.
Develop and maintain data models that support marketing analytics and reporting needs.
Collaboration & Stakeholder Engagement
Work closely with marketing analysts, data scientists, and cross-functional teams to understand data requirements and deliver solutions that drive business insights.
Translate complex business requirements into technical specifications and data architecture.
Data Quality & Governance
Implement data quality checks and monitoring to ensure the accuracy and integrity of marketing data.
Adhere to data governance policies and ensure compliance with data privacy regulations.
Continuous Improvement & Innovation
Stay abreast of emerging technologies and industry trends in data engineering and marketing analytics.
Propose and implement improvements to existing data processes and infrastructure
Years of Experience
5 Years in Data Engineer space
Education Qualification & Certifications
B.Tech or MCA
Skill Set Required
Experience
Proven experience with Apache PySpark, GCP (including Dataproc, BigQuery, Cloud Composer), and data pipeline orchestration.
Technical Skills
Proficiency in SQL and Python.
Experience with data modeling, ETL/ELT processes, and data warehousing concepts.