Data Engineering Team Lead

Steward Partners; Florham Park (NJ); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Steward Partners Global Advisory seeks a Data Engineering Team Lead to design, build, and deliver scalable cloud and data architectures. You will guide a team of data engineers and collaborate with cross-functional teams to fortify data infrastructure, CI/CD pipelines, and analytics capabilities.

You will lead architecture discussions, conduct POCs, and create roadmaps while mentoring engineers and delivering demos to technical audiences.

Qualifications

• Bachelor’s or master’s degree in computer science, engineering, or a related field.

Responsibilities

• Apply advanced Data Engineering principles to design and implement data loading and aggregation frameworks.

Skills

Data pipelines

SQL

Python

Spark

Data modeling

Leadership

Architecture design

CI/CD

Education

Bachelor’s or Master’s degree in CS/Engineering

Tools

Azure

Eventhub

Kafka

dbt

ADF

Airflow

Fivetran

Matillion

Databricks

Synapse Analytics

Job description

Steward Partners Global Advisory is an employee-owned, full-service leading independent private financial services firm, with professionals delivering multifaceted financial solutions and comprehensive service to our clients and their families.

Steward Partners Global Advisory caters to family, institutional and multigenerational investors delivering comprehensive wealth planning and investment strategy implementation, professional asset management services, private banking, institutional consulting, international advisory and business solutions. We pride ourselves on delivering wide-ranging client service with an unwavering commitment to excellence.

Position Overview:

We’re seeking a Data Engineering Team Lead who thrives at the intersection of data engineering solutions. This is a technical leadership role where you’ll design, build, and deliver scalable cloud and data architectures for enterprise clients. You will take the lead in guiding a team of data engineers, fostering collaboration with cross-functional teams, and spearheading initiatives geared towards fortifying our data infrastructure, CI/CD pipelines, and analytics capabilities.

Duties and Responsibilities:

• Apply advanced knowledge of Data Engineering principles, methodologies and techniques to design and implement data loading and aggregation frameworks across broad areas of the organization.
• Design and implement end-to-end data solutions that are secure, performant, and scalable.
• Lead architecture discussions, conduct POCs, create technical roadmaps, diagrams, and solution documentation.
• Gather and process raw, structured, semi-structured and unstructured data using batch and real-time data processing frameworks.
• Experience building enterprise data warehouses using modern data stack tools such as Databricks, platforms like Azure and streaming/integration tech (Eventhub, Kafka, dbt, ADF.)
• Leverage strong Python, Spark, SQL programming skills to construct robust pipelines for efficient data processing and analysis.
• Implement data modeling techniques to design and optimize data schemas, ensuring data integrity and performance.
• Drive continuous improvement initiatives to enhance performance, reliability, and scalability of our data infrastructure.
• Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and translate them into technical solutions.
• Implement best practices for data governance, security, and compliance to ensure the integrity and confidentiality of our data assets.
• Guide and mentor engineers, helping elevate their technical expertise.
• Deliver presentations and demos that clearly communicate solutions to technical audiences.

Skills, Experience & Qualifications:

• Bachelor’s or master’s degree in computer science, Engineering, or a related field.
• Proven experience (8+) in a Solutions Architect/data engineering role, with expertise in designing and building data pipelines, ETL processes, and data warehouses.
• Strong proficiency in SQL, Python and Spark programming languages.
• Strong experience with Azure cloud platform is a must.
• Familiarity with streaming tools (Eventhub, Kafka, Spark), orchestration (Airflow), and data integration technologies (Fivetran, Matillion, ADF.)
• Knowledge of data lake and data warehouse solutions, including Databricks, Synapse Analytics, Azure Data Factory, Airflow etc.
• Solid understanding of data modeling concepts, data warehouse architectures, and data management best practices.
• Excellent communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and drive consensus on technical decisions.
• Relevant certifications (e.g., Azure, databricks, snowflake) would be a plus.

Reports To:

Director of Data Engineering

Direct Reports:

None

Location:

Commutable to the Florham Park, NJ office 1-2 days per week.