Enterprise Data Lake Platform Lead

Accion Labs; Dallas (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

Accion Labs seeks an Enterprise Data Lake Technical Lead to own the design and delivery of a scalable, secure data lake platform across analytics, reporting, and operations. You will lead architectural decisions, mentor teams, and collaborate across security, product, and data engineering to enable self-serve data discovery and governed data workflows.

Responsibilities include building real-time and batch ingestion pipelines, optimizing Delta Lake and Spark, and deploying containerized services

Qualifications

• 5+ years with Apache Kafka (streaming, Connect, Schema Registry).
• 3+ years with Databricks (Delta Lake, Spark optimization, Unity Catalog).
• Deep understanding of data lake architecture patterns.
• 3+ years with DataHub or similar metadata platforms.
• 3+ years with Kubernetes and Terraform.
• 5+ years with enterprise RDBMS (SQL Server, PostgreSQL).
• 5+ years with Azure or AWS cloud services.
• Strong SQL skills and data integration experience.
• CDC patterns and implementation experience.

Responsibilities

• Own the design and implementation of enterprise-scale data lake solutions on Azure/AWS.
• Provide technical mentorship to data engineering and platform teams.
• Drive governance, ingestion, storage, processing, and security layers.
• Lead architectural alignment with Architecture and Product Management.
• Develop data catalog capabilities and metadata-driven data operations.
• Ensure platform reliability, observability, and cost optimization.

Skills

C#

Go

Python

Bash

Leadership

Architecture

SQL

Tools

Kafka

Databricks

DataHub

Terraform

Kubernetes

Azure

AWS

Job description

Accion Labs seeks an Enterprise Data Lake Technical Lead to own the design and delivery of a scalable, secure data lake platform across analytics, reporting, and operations. You will lead architectural decisions, mentor teams, and collaborate across security, product, and data engineering to enable self-serve data discovery and governed data workflows.

Responsibilities include building real-time and batch ingestion pipelines, optimizing Delta Lake and Spark, and deploying containerized services