Lead Data Engineer
We are seeking a Lead Data Engineer to lead our Data Architecture and Data Engineering strategy and execution, delivering world-class solutions that run our business today and scale for the future. This is a key leadership role on the data team and is focused on innovation and delivery, not maintenance.
Role and Responsibilities:
BOTH leadership and hands-on experience.
You will be a thought leader in evaluating and recommending best practices.
You will also be hands-on in implementing these best practices.
Provide technical leadership and mentorship to a team of data engineers, fostering a culture of collaboration, innovation, and continuous learning.
Define and build a new Data Architecture.
Evaluate and challenge the current architecture based on your prior experience and justify your recommendations. Don’t just accept the status quo.
Become an expert on all aspects of Dynatron data.
Weave Data Quality into EVERY aspect of our data architecture. A customer should never find a quality issue before we do.
Design, implement and automate best-of-breed data pipelines using platforms such as Snowflake, AWS, Python, Airbyte/Fivetran, Airflow, and Stored Procedures.
Design, model and implement data warehouses on the Snowflake platform. You MUST have expert experience in Snowflake.
Collaborate closely with cross-functional teams, including product owners, software engineers, data scientists and business stakeholders, to understand data requirements and deliver solutions that meet evolving business needs.
Lead by example, demonstrating a commitment to excellence, integrity, and professionalism in all aspects of your work.
Minimum Qualifications:
- Minimum 10 years hands-on experience in data engineering with a minimum of 4 years in a lead role
- Bachelor Degree or equivalent experience in Data Engineering or Computer Science
- Unimpeachable technical knowledge in Data Engineering and Architecture
- Strong hands-on experience with data infrastructure technologies such as Airflow, Fivetran, Kafka, dbt, and modern data warehouses (e.g., Snowflake, Databricks, and Redshift)
- Proficiency in Python, SQL, and data modeling techniques
- Experience with AWS cloud platform
- Deep understanding of data architecture, pipelines, warehousing, and real-time data streaming
- Proven leadership and team management abilities
- Strategic thinking and ability to align Data with business goals
- Understanding of industry regulations and compliance requirements
- Soft skills
- Critical thinking skills
- Ability to support your position without rigidity
- Can handle differing opinions with professionalism
- Impeccable communication skills
- Excellent presentation skills
- Unquestioned integrity
- True understanding of sense of urgency
- Natural understanding of what it takes to be a go-getter
- What does the interview process look like?
Our interview process is designed to identify high-performance individuals. It typically includes the following steps: Recruiter screening90 Min - Interview #1 is a culture-fit interview with some sanity checks of your skillset90 Min - Interview #2 is a technical interview to probe your knowledge. This role is not a hands-on technical role day-to-day, but you need to be technically sound to lead technical people and especially to lead strategy.30 Min - Interview #3 is rare but may occur for clarifications Salary Range
$140,000 - $170,000 Seniority level
Mid-Senior level Employment type
Full-time Job function
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