Description
Project Description: Our client is a widely-known American company that is working on tools and advice for you to make it easy to pay off debt, choose the best of the best financial products and services (insurance, credit cards, etc.), and tackle your major life goals (saving for retirement, buying a house, etc.). Lead Data Engineer will play a critical role in leading and managing a team of data engineers to deliver high-quality products and features on time and within budget. This role requires strong technical expertise equivalent to a Staff Engineer level, along with good management skills to drive team performance, foster collaboration, and ensure effective communication with stakeholders.
\n- Actual engineering work including some knowledge sharing with other team members.
- Technical Leadership: Leading a team of 5 middle engineers, helping them to deliver from a technical standpoint more efficiently. Be a point of contact with the team manager as a person who is responsible for the team tech delivery.
- Tech Lead Skills: Provide regular feedback to team members. Conduct effective 1:1 meetings. Delegate work effectively, leveraging the strengths of the team members.
- Product Delivery and Quality Assurance: Consistently deliver quality products and features on time and on budget, adhering to established quality measures and standards. Enforce software hygiene practices such as code reviews, testing, and ensuring site reliability to maintain high product standards.
- Project Oversight: Oversee the assignment of work, communication with partners, and ensure timely delivery of projects. Accurately scope work, establish delivery dates, and define quality measures to ensure project success.
- Stakeholder Communication and Collaboration: Communicate project and product status effectively to all stakeholders, providing regular updates and addressing any concerns or challenges. Identify opportunities for leveraging existing team, tools, and processes to improve efficiency and effectiveness in project delivery.
- Python (Pandas, Pyspark, Numpy).
- ETL (Airflow, Snowflake).
- Data Warehouse.
- AWS (Managed Services good to have knowledge RDS, DMS, Kinesis).
- SQL oriented DBS (Mysql, postgres, mariaDB, auroraDB).
- SQL querying pro (optimize, understand of functions).
- Message oriented systems (Kafka, SQS, Kinesis).
- Hands on experience with Data Pipelines debug.
