Tidal Financial Group

Lead Data Engineer

Tidal Financial Group

full-time

Posted on:

Location Type: Remote

Location: Remote • Florida, Illinois, New York, Wisconsin • 🇺🇸 United States

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Job Level

Senior

Tech Stack

AirflowAmazon RedshiftAWSCloudETLKafkaPythonSQL

About the role

  • Design, build, and optimize scalable data pipelines and architectures in AWS (or equivalent).
  • Integrate complex financial data sources—Bloomberg APIs, custodial feeds, and fund administration data—into reliable, auditable data flows.
  • Develop and maintain a modular, well-documented data ecosystem supporting analytics, reporting, and operations at scale.
  • Implement automated data validation and testing frameworks (e.g., Great Expectations or similar).
  • Establish proactive monitoring and alerting for data pipeline performance, reliability, and accuracy.
  • Define and enforce standards for data lineage, versioning, and documentation within the engineering environment.
  • Partner with sales, operations, and trading teams to define data requirements and ensure actionable insights.
  • Provide hands-on technical guidance to data engineers and analysts, promoting best practices in coding, data modeling, and system design.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related experience in a technical field.
  • 7+ years of professional experience in data engineering, including leadership or senior-level design responsibilities.
  • Experience building and scaling cloud-based data architectures in financial or fintech environments.
  • Expert in Python and SQL for data transformation, pipeline orchestration, and automation.
  • Deep knowledge of data warehousing (Snowflake, Redshift, or equivalent) and cloud platforms (AWS preferred).
  • Experience with modern orchestration and transformation tools (Airflow, dbt, Prefect).
  • Familiarity with APIs, event-driven pipelines (Kafka or Kinesis), and ETL frameworks.
  • Strong grasp of version control (Git/GitHub), CI/CD, and Agile methodologies.
  • Familiarity with financial datasets (ETFs, trading, market data) and API integrations (Bloomberg, custodians, fund admins).
Benefits
  • Professional development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
data engineeringPythonSQLdata warehousingcloud-based data architecturesdata transformationpipeline orchestrationautomated data validationdata modelingsystem design
Soft skills
leadershiptechnical guidancecollaborationbest practices promotion