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Data Engineering Technical Lead - VP

Ledgent TechnologyUnited States🇺🇸United StatesPosted 3 Sept 2026

Why This Role Stands Out

This Data Engineering Technical Lead role offers a significant opportunity to shape a modern, cloud-native data platform, driving innovation in analytics and AI, with a competitive compensation package of $125-$150k plus bonus and RSUs. You'll thrive here if you have a passion for designing scalable data pipelines, a knack for evaluating emerging technologies, and possess strong leadership skills to guide modernization efforts. Embrace this chance to make a substantial impact and advance your career.

Quick Overview

Seniority
Leader
Work mode
On Site
Location
United States
Posted
Yesterday
SQLScalaETLAirflowApacheApache SparkAzureBigQueryDatabricksGoogle CloudJavaKafkaPythonVaultdbt

Job Description



Full Time/ Direct Hire


No C2C or 3rd Party Candidates


Client would prefer this person sits onsite at one their locations but is open to remote for the right person


Target Salary is $125-$150k, plus 20% bonus in the form of 10% Cash and 10% RSU's


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.




All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, Los Angeles County Fair Chance Ordinance, and San Francisco Fair Chance Ordinance.

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