Data Engineer

About Anteriad

We are not just another B2B solution provider. We're problem solvers. We believe that data is the key to unlocking effective solutions that span a range of marketing challenges - from customer acquisition to demand generation to account-based marketing. Data is at the core of everything we do. Our team works tirelessly to create powerful solutions that drive real results for our clients. Whether it's through innovative technology or deep analysis, we're committed to finding the best path to growth for every one of our customers.

Why Join Our Data Integration Team?

This is an excellent opportunity for an intelligent, energetic, and self-motivated individual to play a vital role within a growing part of Anteriad. As our Data Engineer, you will have an important role in receiving, organizing, and loading data into Anteriad’s Data Warehouse to be used by our clients and throughout the Anteriad organization. As an integral part of the Data Integration team, you will play a key role in building, managing, and optimizing data pipelines that support our marketing and analytics efforts. You will be a professional with deep expertise in SQL and hands-on experience with SSIS and cloud-based data solutions, especially within the Azure ecosystem.

Anteriad means “always moving forward” and we apply that to our company culture by tirelessly promoting an environment that allows our employees to thrive:

• Work from home
• Training & development with unlimited access to Percipio LMS
• Mix of collaborative & independent work
• Community outreach via Anteriad Cares - encouraging staff to take time to volunteer
• Professional mentoring program - career guidance from leadership
• Employee Resource Groups - collaborate with others that share your passions!

What You’ll Do

• Partner with technical and non-technical stakeholders to translate business requirements into scalable, reliable, and maintainable data engineering solutions.
• Design, develop, and maintain data integration solutions using Microsoft SQL Server, Azure Data Factory, Azure Databricks, Microsoft Fabric, and related Azure services.
• Build, manage, and optimize ETL/ELT pipelines using Azure Data Factory and Microsoft Fabric Pipelines, including pipeline orchestration, parameterization, scheduling, monitoring, and error handling.
• Develop and maintain data transformation logic using Azure Databricks notebooks and Microsoft Fabric notebooks, with a focus on performance, scalability, reusability, and operational reliability.
• Design and implement data ingestion, transformation, validation, and delivery processes across structured, semi-structured, and external data sources.
• Develop and optimize data integration processes utilizing Azure Data Factory, Azure Databricks, Azure Storage Accounts, Azure Data Lake Storage, Azure Key Vault, Microsoft Fabric Lakehouses, Warehouses, Pipelines, and Notebooks.
• Build and maintain SQL-based data models, stored procedures, views, automation scripts, and database objects to support operational and analytical workloads.
• Support the modernization and migration of legacy data integration processes from SSIS and on-premises platforms to cloud-based Azure and Microsoft Fabric architectures.
• Design and implement reusable pipeline patterns, data quality checks, validation controls, logging, alerting, and performance monitoring processes.
• Support new client onboarding efforts by designing and implementing reliable data ingestion, transformation, reconciliation, and validation workflows.
• Troubleshoot and resolve data pipeline, data quality, performance, and integration issues in collaboration with teams across Intelligence & Analytics.
• Design, develop, and maintain datasets, semantic models, and data structures that support reporting, analytics, and visualization solutions across Power BI, Excel, Microsoft Fabric, and other business intelligence platforms.
• Contribute to data engineering standards, documentation, best practices, and reusable frameworks that improve scalability, maintainability, and operational efficiency.
• Research, evaluate, and recommend emerging technologies and platform capabilities that improve data architecture, automation, performance, and reliability.

What You’ll Bring

• 3+ years of experience in data engineering, data integration, business intelligence engineering, or a related technical role.
• 3+ years of experience writing, optimizing, and troubleshooting SQL, including T-SQL, stored procedures, views, indexing strategies, and query performance tuning.
• Hands-on experience designing, building, and supporting ETL/ELT pipelines using Azure Data Factory and/or Microsoft Fabric Pipelines.
• Hands-on experience developing data processing and transformation logic using Azure Databricks notebooks, Microsoft Fabric notebooks, PySpark, Spark SQL, Python, or similar technologies.
• Strong Microsoft SQL Server and relational database design principles skills.
• Experience with Azure data platform services such as Azure Data Factory, Azure Databricks, Azure Storage Accounts, Azure Data Lake Storage, Azure Key Vault, and related cloud data services.
• Strong knowledge and in depth work with Microsoft Fabric components such as Pipelines, Notebooks, Lakehouses, Warehouses, Dataflows, and semantic models.
• Experience building reliable data ingestion and transformation processes from APIs, flat files, databases, web services, cloud storage, and other external data sources.
• Hands on experience implementing data validation, reconciliation, monitoring, logging, and alerting processes for production data pipelines.
• Experience supporting production data workloads, including troubleshooting failures, optimizing performance, and improving pipeline reliability.
• Prior experience modernizing or migrating legacy ETL processes from SSIS, SQL Server, or on-premises environments to Azure or Microsoft Fabric is strongly preferred.
• Bachelor’s degree in Computer Science, Information Technology, Data Analytics, a related field, or equivalent professional experience.
• Power BI, semantic models, or other data visualization and analytics tools experience is a plus.
• Experience with Customer Data Platforms, CDPs, database marketing, marketing analytics, or client data onboarding environments is a plus.
• Working knowledge with AWS or Google Cloud Platform is a plus.
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent verbal and written communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
• Ability to work independently on moderately complex data engineering tasks while collaborating effectively in a team-oriented environment.