Senior Data Engineer: Azure Data Pipelines & ML Ops

Waltech; Waltham (MA); On-site; USD 120,000 - 170,000; Full time

Job summary

Waltech in the United States is seeking a seasoned Data Engineer to build and maintain robust data ingestion pipelines and collaborate with data scientists to translate requirements into scalable solutions. You will own data models, data quality, and production-grade code, while working with Azure or AWS environments.

The role emphasizes hands-on development, knowledge of ETL/ELT, and experience with containerized deployments (Docker/Kubernetes) on cloud platforms.

Qualifications

• Bachelor’s degree in a computer science or quantitative field.
• 5+ years of experience in a Data Engineer role.
• 5+ years’ experience in advanced data processing and software development.
• Experience deploying pipelines using Apache Airflow.
• Proficient/expert level hands-on knowledge of shell scripting, Python, SQL, Azure, or AWS.
• Experience in extracting data using REST APIs and from databases (Oracle, MSSQL).
• Experience with Dockers and Kubernetes are pluses.
• Ideally experience administering Windows and/or Linux servers.
• Be intellectually curious and enjoy learning.

Responsibilities

• Work with data scientists to specify data requirements for data science projects.
• Work with data owners to understand data schema and data flow, develop data dictionaries.
• Develop a deep understanding of ingested data from a business perspective.
• Design robust, scalable, and maintainable data ingestion ETL/ELT pipelines.
• Choose appropriate data models and ensure ingested data quality.
• Write high quality code with high test coverage.
• Supervisory/interpersonal experience and project management experience.

Skills

Data engineering

Python

SQL

Apache Airflow

Azure

AWS

ETL/ELT pipelines

Docker

Kubernetes

REST APIs

Windows/Linux servers

Education

Bachelor’s degree in Computer Science

Tools

Azure

AWS

Airflow

Docker

Kubernetes

Job description

Waltech in the United States is seeking a seasoned Data Engineer to build and maintain robust data ingestion pipelines and collaborate with data scientists to translate requirements into scalable solutions. You will own data models, data quality, and production-grade code, while working with Azure or AWS environments.

The role emphasizes hands-on development, knowledge of ETL/ELT, and experience with containerized deployments (Docker/Kubernetes) on cloud platforms.