Lead Data Engineer (Snowflake/Dbt)

TL;DR

Lead Data Engineer (Snowflake/DBT): Building and running data pipelines and services to support business functions, reports, and dashboards with an accent on data extraction, processing, and analysis in a Data Mesh architecture. Focus on improving data pipeline delivery, troubleshooting design challenges, and translating business requirements into technical specifications.

Location: Can work remotely from home or anywhere in their assigned Indian state. Additionally, you can work from a different country or Indian state for 90 days of the year.

Company

hirify.global is building a business management platform designed to save small businesses time and money, providing business accounts and connected administrative solutions.

What you will do

• Develop end-to-end ETL/ELT pipelines, collaborating with Data Analysts.
• Design and implement scalable, automated processes for data extraction, processing, and analysis in a Data Mesh architecture.
• Mentor junior engineers and act as a go-to expert for data technologies.
• Troubleshoot and resolve technical issues, improving data pipeline delivery.
• Translate business requirements into technical requirements, owning data models and reports end to end.
• Apply and champion data warehouse governance, ensuring data quality and coding best practices.

Requirements

• 7+ years of extensive development experience using Snowflake or similar data warehouse technology.
• Working experience with DBT and other modern data stack technologies like Snowflake, Apache Airflow, Fivetran, AWS, Git, and Looker.
• Experience in agile processes such as SCRUM.
• Extensive experience in writing advanced SQL statements and performance tuning.
• Experience in data ingestion techniques using custom or SaaS tools like Fivetran.
• Experience in data modeling and optimizing existing/new data models.

Nice to have

• Experience architecting analytical databases in a Data Mesh architecture.
• Experience with Python, governance tools (e.g., Atlan, Alation, Collibra), or data quality tools (e.g., Great Expectations, Monte Carlo, Soda).
• Experience working in a digitally native company, ideally Fintech.

Culture & Benefits

• Flexible workplace model supporting both in-person and remote work.
• Competitive salary, self & family health insurance, and term & life insurance.
• Learning & development budget and WFH setup allowance.
• 15 days of privilege leaves, 12 days of casual leaves, and 12 days of sick leaves.
• 3 paid days off for volunteering or L&D activities and stock options.