Senior Data Engineer & Tech Lead — Finance Data Pipelines

Sophus IT Solutions

Frisco (TX)

On-site

USD 140,000 - 190,000

Full time

7 days ago
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Job summary

Sophus IT Solutions in Frisco, TX seeks a Senior/Lead Data Engineer to architect and lead enterprise data pipelines for finance and revenue data using Snowflake, Databricks, Python/PySpark and advanced SQL. You will define standards for batch, streaming, and CDC ingestion, and ensure scalable, fault-tolerant designs on Azure.

You will provide technical leadership across multiple teams, guide data modeling and governance, and implement CI/CD and observability.

Qualifications

  • Experience architecting enterprise-scale ELT/ETL pipelines for finance and revenue data.

Responsibilities

  • Architect, design, and oversee enterprise-scale ELT/ETL pipelines for finance and revenue data (billing, revenue, GL, opex).
  • Define and enforce standards for batch, incremental, and streaming ingestion patterns (CDC, watermarking, event-driven ingestion).
  • Ensure idempotent, fault-tolerant, and highly scalable pipeline design across platforms.
  • Establish frameworks for error handling, retry strategies, dead-letter queue patterns, and operational resiliency.
  • Provide technical leadership for multi-source, high-volume data integration pipelines.
  • Lead architecture and adoption of Snowflake and Databricks platforms for large-scale data processing and analytics.

Skills

Snowflake
Databricks
PySpark
Python
Advanced SQL
Azure
CI/CD
Airflow
Azure Data Factory
Terraform
Bicep
Great Expectations
dbt
Kafka

Tools

Airflow
Azure Data Factory
Terraform
Bicep
Great Expectations
dbt
Kafka

Job description

Sophus IT Solutions in Frisco, TX seeks a Senior/Lead Data Engineer to architect and lead enterprise data pipelines for finance and revenue data using Snowflake, Databricks, Python/PySpark and advanced SQL. You will define standards for batch, streaming, and CDC ingestion, and ensure scalable, fault-tolerant designs on Azure.

You will provide technical leadership across multiple teams, guide data modeling and governance, and implement CI/CD and observability.

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