Zinnia - Associate Director - Data Engineering

What Youll Do : - Oversee the technological choices and implementation of data pipelines and warehousing strategies - Design data sets that are simple, maintainable, and enable Data Analysts, Data Scientists, and stakeholders to work efficiently with data - Lead cross-organizational efforts aimed at automating our data processes and data-as-a-service capabilities - Advocate for and implement technical best practices throughout the data organization to ensure high-quality outcomes - Mentor data team members fostering a culture of learning and continuous improvement - Partner with other leaders to bring innovative concepts to reality and design data models for downstream data maximization - Ensure reliability in data pipelines and enforce data governance, security, and protection of customer information while balancing technical debt. - Evaluate and champion new engineering tools that enhance efficiency and scalability within the Youll Need : - A Bachelor/Masters Degree in Computer Science or related field with 10 years of experience in Data Engineering. - Extensive experience with data engineering techniques, including proficiency in Python and SQL. - You are acquainted with designing custom Machine Learning (ML) pipelines that integrate into production environments that are customer facing. - You have experience working on product teams but also collaborating with other data science team members. - You can communicate with a team and articulate ideas to both team members and non-technical stakeholders. - Strong Working knowledge of Airflow, dbt, Jira, Git, and Data Warehousing tools (BigQuery, Snowflake) - Experience in tools such as GitHub Actions, Terraform, containers - Proven track record in leading data engineering teams, mentoring staff, and promoting a culture of learning and teaching. - Demonstrated ability to take risks when seeking novel solutions to complex problems and to persist in the face of You Will Use & Must Be Well-versed With : - Python for data pipelining and automation - Airbyte and Airflow for ETL purposes. - GCP or AWS platforms utilizing tools like Terraform, Container services (GKE/EKS), Cloud Functions / Lambda, BigQuery/Snowflake - dbt for data modeling. - PowerBI for data visualization and consumer-facing dashboard (ref:hirist.tech)

Location: noida, IN

Posted Date: 5/10/2025