Manager, Data Engineer

Burtch Works; New York (NY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Burtch Works is seeking a hands-on Manager of Data Engineering in the New York area. You will build and optimize data pipelines that connect core systems (financial, HR, gaming, operational) to planning and reporting apps, focusing on Python, SQL Server/T‑SQL, ETL/ELT, and REST APIs.

You will work across Linux and Windows in a data-driven environment, implementing data quality checks and orchestration patterns, while improving reliability and observability of the enterprise data platform.

Qualifications

• Hands-on experience building production data pipelines in enterprise environments.
• Strong Python and SQL coding skills for data integration and troubleshooting.
• Experience with SQL Server, T‑SQL, stored procedures, jobs, and bulk loading.

Responsibilities

• Build and maintain ETL/ELT pipelines ingesting data into a SQL Server data warehouse.
• Develop pipelines within Medallion Architecture with data quality checks.
• Write production-grade Python with pandas and DB connectivity libraries.

Skills

Python development

Pandas

SQL Server

T‑SQL

ETL/ELT

REST API

Dagster/Airflow/Prefect

Linux/Windows

Data quality

Observability

Education

Bachelors in CS/Engineering/IS/Data Analytics

Tools

pyodbc

SQLAlchemy

SQL Server Management

OpenTelemetry

Loki

Grafana

Job description

About The Company

We are a leading entertainment and hospitality organization operating in a highly data-intensive environment spanning gaming, finance, workforce operations, and enterprise planning. As the organization continues to modernize its data ecosystem, the Data & Analytics team is building scalable pipelines and integrations that improve how critical business data moves across enterprise systems and becomes available for planning, reporting, and decision-making. This is an opportunity to join a growing data organization and contribute directly to the continued modernization, reliability, and scalability of its enterprise data platform.

Job Title

Manager of Data Engineering

Location

Hybrid - Queens, NY

Job Summary

The Manager of Data Engineering will be a hands-on engineer responsible for building, maintaining, and improving the data pipelines connecting core enterprise systems—including financial, HR, gaming, and operational platforms—to downstream planning and reporting applications. This role is heavily focused on Python, SQL Server/T-SQL, ETL/ELT development, workflow orchestration, and REST API integrations. You'll work within an established orchestration and infrastructure environment, developing reliable pipelines while helping advance a newly established Medallion Architecture and its associated data quality standards. The ideal candidate is a strong hands-on engineer and complex problem solver who is comfortable investigating production issues, understanding existing systems, and independently determining how to move data reliably between platforms. This is not an architecture-only position—you'll be writing Python and SQL, building integrations, troubleshooting pipelines, and working directly with enterprise data every day.

Key Responsibilities

• Build and maintain ETL/ELT pipelines that ingest financial, HR, gaming, and operational data into a SQL Server data warehouse.
• Develop pipelines within a newly established Medallion Architecture, implementing appropriate data validation and quality checks throughout each layer.
• Write production-quality Python using pandas and database connectivity frameworks such as pyodbc, SQLAlchemy, or similar technologies.
• Develop and maintain T-SQL stored procedures, SQL Agent jobs, and BULK INSERT/MERGE-based data loading processes.
• Build integrations that deliver validated enterprise data into downstream planning and reporting platforms through REST APIs.
• Develop and schedule pipeline workflows using established orchestration patterns, including assets, sensors, schedules, concurrency controls, and pools.
• Build comparison and reconciliation scripts that validate data across environments and incorporate automated data quality checks directly into event-driven pipelines.
• Monitor pipeline health through existing observability tools and dashboards, including OpenTelemetry, Loki, and Grafana, while adding appropriate logging to newly developed pipelines.
• Troubleshoot pipeline failures, data discrepancies, transaction issues, concurrency problems, and other complex production incidents through root-cause analysis.
• Work across both Linux and Windows environments to support enterprise data integrations and production workloads.
• Partner with Data, Analytics, Finance, HR, Gaming, and other business stakeholders to understand data requirements and deliver reliable solutions.
• Contribute to the continued improvement of engineering standards, documentation, data quality, observability, and overall platform reliability.

Education

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Analytics, or a related technical discipline preferred.

Experience

• 3–5+ years of professional experience building production data pipelines, integrations, or backend data systems.
• Demonstrated hands-on experience developing ETL/ELT pipelines using Python and SQL within enterprise data environments.
• Strong experience with SQL Server and T-SQL, including writing, maintaining, and debugging stored procedures and working with SQL Agent jobs.
• Experience with workflow orchestration platforms such as Dagster, Airflow, Prefect, or similar technologies.
• Experience integrating applications and data platforms through REST APIs, including authentication, request/response handling, and error management.
• Experience working across Linux and Windows environments.
• Proven ability to independently troubleshoot complex data and production issues and drive problems through root-cause resolution.

Skills

• Strong hands-on Python development skills, including experience using pandas for data transformation and pyodbc, SQLAlchemy, or similar libraries for database connectivity.
• Strong SQL Server and T-SQL capabilities with the ability to develop and troubleshoot stored procedures, data loads, transactions, SQL Agent jobs, and BULK INSERT/MERGE patterns.
• Solid understanding of modern ETL/ELT architecture and data engineering principles, including Medallion Architecture, data quality, reconciliation, and scalable pipeline development.
• Experience working with workflow orchestration technologies and the ability to develop within established scheduling, event-driven, concurrency, and dependency-management patterns.
• Strong API integration capabilities with experience moving data between enterprise platforms through REST APIs and managing authentication, file transfers, job status polling, and error handling.
• Strong troubleshooting and complex problem-solving skills with the ability to investigate subtle production issues involving data integrity, pipeline performance, transactions, or concurrency.
• Understanding of observability and production monitoring concepts, including structured logging, metrics, dashboards, and tools such as OpenTelemetry, Loki, and Grafana.
• Strong communication and collaboration skills with the ability to work effectively with both technical teams and business stakeholders while independently owning engineering deliverables.

Preferred Qualifications

• Experience integrating enterprise planning, financial planning, or FP&A platforms through REST APIs, including chunked file uploads and polling for long-running processes.
• Experience extracting and integrating data from HR, payroll, or workforce management platforms such as Workday, UKG, or similar enterprise systems.
• Experience building observability capabilities, including structured logging, metrics pipelines, monitoring queries, and production dashboards.
• Experience owning infrastructure or data migrations across platforms and environments while maintaining data integrity and minimizing downtime.
• Demonstrated experience diagnosing complex production incidents through root-cause analysis rather than simply resolving immediate symptoms.
• Familiarity with Agentic Coding workflows and Model Context Protocol (MCP) integrations is a plus.

Why Join Us

This is an opportunity to play a hands-on role in the continued modernization of an enterprise data environment supporting some of the organization's most critical financial, workforce, gaming, and operational systems. You'll work across the full data pipeline—from ingestion and transformation through orchestration, quality, observability, and downstream integration—while helping establish engineering practices that will support the organization's next phase of data and analytics maturity. If you're a builder who enjoys solving difficult data problems, writing production code, and improving the reliability of complex enterprise systems, this role offers the opportunity to make a meaningful impact within a growing Data & Analytics organization.