Lead Data Engineer

TechDigital Group; Providence (RI); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player seeks a Senior Technical Lead to guide teams in developing innovative data solutions using Snowflake, DBT, SQL, and Python. This pivotal role involves overseeing the design and implementation of data models and ETL pipelines, ensuring high performance and data integrity. The ideal candidate will have extensive experience in cloud data engineering, particularly in the healthcare sector, with a strong focus on data governance and HIPAA compliance. Join a dynamic team where your leadership and technical expertise will drive impactful data solutions that meet critical business needs.

Qualifications

• 8+ years of experience in cloud native data engineering, focusing on Snowflake and DBT.
• Proven experience in designing and optimizing data warehouse solutions.

Responsibilities

• Lead the design and implementation of ETL pipelines for healthcare data.
• Mentor junior engineers and collaborate with cross-functional teams.

Skills

Snowflake

DBT

SQL

Python

Problem-solving

Leadership

Tools

Azure

Matillion

Job description

ETL Developer, Data Engineer with strong DBT ETL tools experience, Azure Cloud experience, Matillion, Data modelling in Snowflake.

Snowflake Senior Technical Lead with SQL, Python, DBT

Job Summary

The Senior Technical Lead will be responsible for leading technical teams and projects related to Snowflake, DBT, SQL, and Python. The role involves overseeing the design, development, and implementation of data solutions leveraging these technologies to meet business requirements.

Key Responsibilities

1. Lead and manage technical teams in the development and implementation of Snowflake data solutions.
2. Design, build, and optimize data models using Snowflake and DBT for efficient data processing.
3. Develop and optimize SQL queries for data extraction, transformation, and loading processes.
4. Utilize Python for scripting and automation of data processes and workflows.
5. Collaborate with cross-functional teams to understand data requirements and ensure the successful delivery of technical solutions.
6. Conduct code reviews, provide technical guidance, and mentor team members to enhance overall technical capabilities.
7. Troubleshoot technical issues and provide resolutions in a timely manner to ensure smooth project execution.

Skill Requirements

1. Proficiency in Snowflake for data warehousing and cloud data platform.
2. Experience with DBT (data build tool) for data transformation and modeling.
3. Strong command of SQL for querying and manipulating data in databases.
4. Proficient in Python programming for scripting, automation, and data manipulation.
5. Excellent problem-solving skills and the ability to communicate effectively with technical and non-technical stakeholders.
6. Strong leadership skills to effectively lead and motivate technical teams towards project success.

Required Skills

Minimum 8+ years of experience in cloud native data engineering, including 3-5 years with Snowflake, Azure, Matillion, DBT ETL tools. Experience in doing data modeling for Data Warehouse in Snowflake. Hands-on experience in designing and developing ELT processes. At least 3-5 years experience working in the healthcare payor domain, with a focus on data governance, HIPAA compliance, and healthcare-related data processing. Proven experience in designing, implementing, and optimizing data warehouse solutions. Strong leadership skills with the ability to mentor and collaborate with diverse teams and stakeholders. Strong understanding of HIPAA compliance requirements for healthcare data security, privacy, and regulatory standards.

Responsibilities

As a Lead Data Engineer, you will lead the design, development, and overall delivery of ETL pipelines to process healthcare data, ensuring efficient, scalable, and high-performance solutions with data consistency and quality. Work closely with cross-functional teams, including data architects, analysts, and business stakeholders to ensure alignment on data requirements. Mentor junior engineers and team members. Address and resolve issues related to ELT processes, ensuring minimal disruptions and maintaining data integrity.