Data Engineering Technical Lead - VP

LEDGENT

San Diego, CA, United States

6 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

3 years minimum

Compensation

$125,000.0 - $150,000.0

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Artificial Intelligence Airflow Data Analysis Microsoft Azure BigQuery Cloud Engineering Data Architecture Information Engineering Extract Transform Load (ETL) Data Systems Data Vault Modeling

+12 more

Python (Programming Language) Software Tools SQL Databases SQL Server Reporting Services SQL Server Integration Services Data Streaming Google Cloud Apache Spark Technical Debt Apache Kafka Data Pipelines Databricks

Job description

The Data Engineering Technical Lead will help shape, modernize, and scale our enterprise data platform. This role is central to their mission of transforming legacy data systems into a modern, cloud-native Lakehouse environment that powers analytics, AI, and business intelligence across the organization. As a technical lead, you will design and deliver scalable data pipelines, define data design patterns, enforce engineering standards, and leverage AI-assisted tools to accelerate modernization, improve productivity, and reduce technical debt. You will drive proofs of concept (POCs) and points of view (POVs) to evaluate emerging technologies and frameworks, ensuring that the platform remains innovative, cost-efficient, and future-ready.

Requirements

Bachelors degree
8+ years of experience in data engineering or related technical fields, with at least 3+ years in a lead or senior role.
Proven experience designing and implementing data design patterns (e.g., CDC, SCD, Medallion, Data Vault, streaming, and batch patterns).
Deep expertise with Databricks, Apache Spark, dbt, Fivetran, Census, Airflow, and Kafka. Solid experience across Azure and/or Google Cloud Platform (e.g., Synapse, Data Factory, BigQuery, Pub/Sub).
Hands-on experience modernizing legacy ETL (SSIS/SSRS) workloads into cloud-native pipelines.
Demonstrated ability to build POCs and POVs that validate new tools, frameworks, or architectures.
Working knowledge of AI-assisted engineering tools for development, observability, or optimization.
Proficiency in SQL and one programming language (Python, Scala, or Java).
Strong problem-solving, architectural thinking, and collaboration skills.
Excellent communicator with the ability to translate technical topics to business stakeholders.