Data Engineering Lead: Snowflake, ADF & Databricks

TechDigital Group; Dallas (TX); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player is seeking a Data Lead to oversee the implementation and support of Snowflake, Azure Data Factory, and Data Bricks solutions. In this pivotal role, you will lead the design and development of data pipelines, ensuring data quality and integrity while mentoring team members on best practices. This position offers the opportunity to stay at the forefront of data engineering and integration, working with cutting-edge technologies in a dynamic environment. If you are passionate about data and eager to drive improvements in data processes, this role is perfect for you.

Qualifications

• Proficiency in Snowflake architecture and optimization.
• Hands-on experience with Azure Data Factory (ADF) and Data Bricks.

Responsibilities

• Lead design and deployment of Snowflake and Azure Data Factory solutions.
• Collaborate with teams to gather data requirements and ensure data quality.

Skills

Snowflake architecture

Azure Data Factory (ADF)

Data Bricks

ETL processes

Data modeling techniques

Problem-solving

Communication skills

Leadership skills

Job description

Business & Stakeholder Engagement
Work closely with business stakeholders (Underwriting, Claims, Actuarial, Finance, Operations) to understand reporting and analytics needs.
Translate business questions and KPIs into data analysis, reports, and dashboards.
Conduct requirement‐gathering sessions and prepare business requirement documents (BRDs) and reporting specifications.
Present insights, trends, and recommendations to business and leadership stakeholders in a clear and concise manner.
Data Analysis & Reporting
Analyze data related to policy lifecycle, claims, premiums, losses, exposure, reserves, and billing.
Develop and maintain dashboards, reports, and scorecards using BI tools (Power BI, Tableau, etc.).
Perform trend analysis, variance analysis, and root‐cause analysis.
Support regulatory, operational, and management reporting.
Validate data accuracy and ensure consistency across reports.
Data Collaboration
Write and optimize SQL queries to extract and analyze data from enterprise systems.
Collaborate with data engineering teams on data availability, data quality, and transformations.
Assist with data reconciliation, data quality checks, and issue resolution.
Document data definitions, business rules, assumptions, and metrics.

above is the JD

Insurance Domain Experience (Mandatory)
Strong hands‐on experience in Insurance (P&C, Life, Annuity, or Reinsurance).
Solid understanding of:
Policy lifecycle (Quote, Bind, Issue, Endorse, Renew)
Claims lifecycle and claims financials
Premiums, losses, reserves, exposure
Billing and invoicing

Experience working with insurance platforms such as Guidewire, Duck Creek, Sapiens, or similar is highly preferred.
Technical & Analytical Skills
Strong experience as a Data Analyst in enterprise environments.
Proficiency in SQL for querying and data analysis.
Hands‐on experience with BI tools:
Power BI (preferred)
Tableau / Qlik (or similar)

Strong experience with Excel (pivot tables, formulas, data analysis).
Experience working with relational databases (SQL Server, Oracle, PostgreSQL).
Familiarity with data warehousing and dimensional models.

Preferred Skills
Exposure to Azure / Cloud data platforms.
Experience with Power BI semantic models, DAX, and Power Query.
Knowledge of data governance, metadata, and data quality frameworks.
Experience working in Agile/Scrum delivery models.
Ability to support executive dashboards and self‐service BI.