L1 Data Engineer – Remote

We are looking for a motivated and technically solid L1 Data Engineer to join our growing Data & Analytics team. In this role, you will be responsible for designing, building, and maintaining the data architecture and infrastructure that supports our organization’s data strategy. You will work hands-on to develop, test, and deploy reliable data solutions — ensuring pipelines are scalable, efficient, and aligned with business requirements.

This is an ideal opportunity for a data professional who is eager to deepen their expertise in cloud-native data platforms, particularly within the Microsoft Azure and Databricks ecosystem, and who thrives in a collaborative, fast-paced environment.

Key Responsibilities

Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support business intelligence and analytics use cases
Build and optimize data ingestion processes using Azure Data Factory and Databricks, ensuring data quality and consistency across all layers of the data platform
Transform and process large datasets using PySpark and Python, applying best practices for performance and maintainability
Write and optimize complex SQL queries to support analytical reporting and data validation requirements
Collaborate with data architects and senior engineers to implement and maintain data models aligned with organizational standards
Monitor, troubleshoot, and resolve pipeline failures and data quality issues, applying root-cause analysis to prevent recurrence
Contribute to documentation of data pipelines, data dictionaries, and engineering standards
Support the team in exploring and evaluating new tools and approaches to continuously improve the data infrastructure

Requirements

2+ years of professional experience in a Data Engineering or closely related role
Strong proficiency in Python for data processing, transformation, and automation tasks
Hands-on experience with Pandas for data manipulation and PySpark for distributed data processing
Practical experience with Databricks, including notebook development, clusters, and job orchestration
Experience building and managing data pipelines with Azure Data Factory
Working knowledge of Azure Synapse Analytics, particularly Spark pool integration
Solid SQL skills, including query writing, optimization, and performance tuning
Familiarity with data engineering principles including incremental loading, data lake architecture, and Delta Lake
Understanding of data governance and security concepts within a cloud data platform

NICE TO HAVE

Experience with SQL Server migration projects, including schema conversion and data movement
Exposure to Terraform for Azure infrastructure provisioning and management
Familiarity with CI/CD practices applied to data engineering workflows
Experience with Delta Sharing or Lakehouse Federation concepts

CERTIFICATION REQUIREMENT

Candidates are expected to hold or be actively working toward the Databricks Certified Data Engineer Associate certification. This certification validates foundational knowledge across the following domains:
Databricks Lakehouse Platform architecture and capabilities
ETL and ELT workflows using Spark SQL and PySpark
Incremental data processing and structured streaming
Production pipeline development and orchestration
Data governance and security within the Databricks environment