Azure Data Engineer — Remote, Pipelines & Lakehouse

Somewhere; United States; Remote; USD 110,000 - 140,000; Full time

Job summary

Somewhere is seeking a Data Engineer (Azure) to own end-to-end data solutions on Azure and Databricks. You will design production-grade pipelines, work directly with U.S. clients and analytics teams, and ensure data quality and governance.

The role requires hands-on experience with Azure Data Factory, Databricks, ADLS, PySpark, and SQL, plus strong Python skills. Remote work aligned to U.S. business hours with a collaborative, distributed team.

Qualifications

• 3+ years in data engineering, big data, or cloud data solutions, including at least 3 years hands-on with Microsoft Azure.
• Strong hands-on experience with Azure Data Factory, Azure Databricks, ADLS, PySpark, Azure SQL Database, Python, and SQL.
• Practical experience building Data Lake or Lakehouse solutions and batch or streaming pipelines.
• Working knowledge of Spark and one or more of: Azure Event Hubs, Kafka, Airflow, or Hadoop.
• Solid grasp of data security, governance, access controls, data quality, source control, CI/CD, and automated deployments.
• Ability to write modular, scalable, maintainable, production‑quality code with strong debugging skills.
• Strong written and spoken English for direct client communication. Native or professional proficiency in Spanish or Portuguese.
• Proven ability to work independently while collaborating effectively with U.S.-based clients and global teams.

Responsibilities

• Design and build scalable data pipelines for both batch and streaming workloads.
• Develop Data Lake and Lakehouse solutions using Azure Data Factory, Azure Databricks, ADLS, PySpark, and Azure SQL Database.
• Build and integrate REST APIs to move and expose data across systems.
• Process, transform, validate, and harmonize structured, semi-structured, and unstructured data.
• Work fluently across Delta Lake, Parquet, Avro, JSON, and CSV formats.
• Implement data-quality controls, validation logic, and exception handling to keep data trustworthy.
• Schedule, monitor, troubleshoot, and optimize pipelines and Spark workloads.
• Build in logging, alerting, and observability so issues are caught before clients notice them.
• Support deployment and monitoring across development, testing, staging, and production environments.
• Collaborate directly with BI, analytics, and Data Science teams with secure access to data.
• Collaborate with clients, architects, consultants, vendors, and development teams.
• Take ownership of deliverables and timelines, and document pipelines and data models for scaling.

Skills

Data engineering

Big data

Cloud data solutions

Client communication

Independent work

Tools

Azure Data Factory

Azure Databricks

ADLS

PySpark

Python

SQL

Spark

Kafka

Airflow

Hadoop

Job description

Somewhere is seeking a Data Engineer (Azure) to own end-to-end data solutions on Azure and Databricks. You will design production-grade pipelines, work directly with U.S. clients and analytics teams, and ensure data quality and governance.

The role requires hands-on experience with Azure Data Factory, Databricks, ADLS, PySpark, and SQL, plus strong Python skills. Remote work aligned to U.S. business hours with a collaborative, distributed team.