IN-Person interview ll Senior Data Engineer ll Manhattan , NY ll Skype

Job Title Senior Data Engineer
Company: XDUCE statement of work or SOW with financial services company

Location 28 Liberty Street in Lower Manhattan or financial district
Interview Process: 2 videos and 1 in-person interview

Work Mode Must work 3 days hybrid in lower NYC.
Duration: 12-24 months

About the Role: We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that power our analytics and machine learning capabilities. You will work cross-functionally with data scientists, analysts, and product teams to ensure data is reliable, accessible, and performant across the organization.

Key Responsibilities:

• Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources.
• Develop and manage data warehouses and data lakes using cloud platforms such as AWS, Google Cloud Platform, or Azure.
• Ensure data quality, integrity, and availability through monitoring, testing, and alerting frameworks.
• Collaborate with data scientists and analysts to understand data needs and deliver optimized data models.
• Optimize query performance and storage efficiency across large-scale distributed systems.
• Define and enforce data governance best practices, including lineage, cataloging, and documentation.
• Partner with engineering teams to integrate data infrastructure with production systems.
• Continuously evaluate and adopt new tools and technologies to improve the data platform.

Required Qualifications

• 8+ years of experience in data engineering, software engineering, or a related field.
• Proficiency in Python for data processing and pipeline development.
• Strong SQL skills and experience with databases (e.g., SQL Server, Oracle, Redshift).
• Experience with big data technologies such as Apache Spark, Kafka, or Flink.
• Hands-on experience with cloud platforms (AWS, Google Cloud Platform, or Azure) and their data services.
• Familiarity with version control (Git) and CI/CD practices.
• Solid understanding of data modeling concepts (star schema, data vault, etc.).
• Strong analytical and problem-solving skills with a focus on data quality and reliability.

Nice to Have:

• Experience with dbt (data build tool) for transformation and data modeling.
• Knowledge of streaming data architectures and real-time processing.
• Familiarity with data observability tools such as Monte Carlo or Great Expectations.
• Exposure to machine learning workflows and feature engineering pipelines.
• Experience working in a fast-paced startup or high-growth environment.