Data Engineering Technical Lead - VP

Ledgent Technology; New York (NY); Hybrid; USD 125,000 - 150,000; Full time

Benefits offered by this job

20% bonus (cash + RSUs)

Job summary

Ledgent Technology is seeking a technical lead in New York to design and deliver scalable data pipelines within a cloud-native Lakehouse. You will drive data design patterns, enforce standards, and evaluate emerging tools to keep the platform innovative and cost-efficient.

The role requires 8+ years in data engineering with 3+ years in a lead role, deep expertise in Databricks/Spark, and hands-on modernization of ETL workloads.

Qualifications

• 8+ years in data engineering with at least 3+ years in a lead role.
• Experience designing data patterns (CDC, SCD, Medallion, Data Vault) and pipelines.
• Deep expertise with Databricks, Spark, dbt, Fivetran, Airflow, Kafka, Azure or GCP.
• Hands-on modernization of legacy ETL workloads to cloud-native pipelines.
• Ability to build POCs/POVs for new tools and architectures.

Responsibilities

• Design and deliver scalable data pipelines and data models.
• Enforce engineering standards and drive modernization efforts.
• Lead POCs/POVs to evaluate new tech and architectures.
• Collaborate cross-functionally to reduce technical debt and improve productivity.

Skills

Data engineering leadership

Architectural thinking

SQL

Python/Scala/Java

Collaboration

Tools

Databricks

Apache Spark

dbt

Fivetran

Airflow

Kafka

Azure

BigQuery

Job description

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:

• 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 GCP (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.