As a Lead Data Engineer at Trellance, you will be responsible for taking a leadership role in designing, building, and maintaining advanced data pipelines and architectures that drive strategic decision-making processes. With your expertise in advanced data platforms, particularly Snowflake and cloud environments, you will provide high-level strategic guidance on best practices, emerging technologies, and innovative solutions. Additionally, you will mentor and lead a team of data engineers, guiding them in their professional development, driving the adoption of best practices, and ensuring that our data solutions are robust, efficient, and aligned with industry standards.

Key Responsibilities :

- Partner with business stakeholders and cross-functional teams to gather requirements and convert them into scalable data solutions.

- Design, build, and maintain robust data pipelines and architectures on Snowflake (on Azure) and Power BI or Tableau.

- Implement and automate data ingestion and transformation workflows using Azure Data Factory (ADF) and ELT best practices.

- Develop and enforce scalable data models, including star and snowflake schema designs, for analytics use cases.

- Create intuitive dashboards and reports using Power BI and Tableau, enabling data-driven decision-making.

- Use Python for data wrangling, automation, and supporting analytics or ML workflows.

- Ensure adherence to data governance, security, and compliance best practices (e.g., GDPR, CCPA).

- Guide and mentor team members, helping them grow technically while fostering collaboration.

- Stay up to date with emerging data engineering trends and introduce innovative solutions where applicable.

Required Qualifications :

- Bachelors or masters degree in computer science, Engineering, Information Technology, or a related field.

- 710 years of experience in data engineering, with hands-on leadership in building and managing large-scale data platforms.

- Proven skills in Snowflake, Power BI and Tableau for building insightful reports and dashboards.

- Proficiency in SQL and PL/SQL and Python, with ability to design and optimize complex queries and procedures.

- Experience in predictive analytics, including working with modelling data, interpreting outputs, and integrating models into data pipelines.

- Good working knowledge of Python for data transformation, scripting, and ML support.

- Deep understanding of data modelling techniques and data warehouse design principles.

- Experience with Git and CI/CD pipelines for code and data solution deployment.

- Excellent communication and leadership skills, with a proven ability to mentor and collaborate across functions.

- Good to have experience with machine learning workflows, including building or supporting predictive models using algorithms like linear regression, decision trees, random forests, and clustering techniques.

- Good to understanding of Azure tenant architecture, services, and Snowflake infrastructure setup and maintenance.

Preferred Qualifications :

- Certifications in Snowflake, Azure, Power BI, or Tableau.

- Exposure to MS Fabric or other modern analytics ecosystems is a plus.

- Familiarity with MLOps practices or deploying machine learning models in production environments.