What Your Responsibilities Will Be

You will Design, develop, and maintain efficient ETL pipelines using DBT,Airflow to move and transform data from multiple sources into a data warehouse.
You will Lead the development and optimization of data models (e.g., star, snowflake schemas) and data structures to support reporting.
You will Leverage cloud platforms (e.g., AWS, Azure, Google Cloud) to manage and scale data storage, processing, and transformation processes.
You will Work with business teams, marketing, and sales departments to understand data requirements and translate them into actionable insights and efficient data structures.
You will Use advanced SQL and Python skills to query, manipulate, and transform data for multiple use cases and reporting needs.
You will Implement data quality checks and ensure that the data adheres to governance best practices, maintaining consistency and integrity across datasets.
You will Experience using Git for version control and collaborating on data engineering projects.

What Youll Need to be Successful

Bachelors degree with 6+ years of experience in Data Engineering.
ETL/ELT Expertise : experience in building, improving ETL/ELT processes.
Data Modeling : experience with designing and implementing data models such as star and snowflake schemas, and working with denormalized tables to optimize reporting performance.
Experience with cloud-based data platforms (AWS, Azure, Google Cloud)
SQL and Python Proficiency : Advanced SQL skills for querying large datasets and Python for automation, data processing, and integration tasks.
DBT Experience : Hands-on experience with DBT (Data Build Tool) for transforming and managing data models.

Good to have Skills:

Familiarity with AI concepts such as machine learning (ML), (NLP), and generative AI. Work with AI-driven tools and models for data analysis, reporting, and automation.
Oversee and implement DBT models to improve the data transformation process.
Experience in the marketing and sales domain, with lead management, marketing analytics, and sales data integration.
Familiarity with business intelligence reporting tools, Power BI, for building data models and generating insights.

Lead Data Engineer