Anteriad

Data Engineer

• 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.

• Build and maintain data ingestion pipelines using Azure Data Factory (ADF) to move data into the corporate Azure Data Lake and related platforms.
• Develop and enhance data transformation logic in Databricks notebooks, primarily leveraging SQL-based transformations in existing SQL scripts and stored procedures.
• Support a medallion data architecture (Bronze, Silver, Gold) with Silver and Gold datasets stored primarily in Parquet format.
• Assist in migrating SQL Server–based processes (scripts, stored procedures, SSIS logic) running on Azure VMs into Azure-native pipelines and Databricks transformations.
• Continuously update and enhance existing database solutions and systems based on new and evolving requirements from marketing campaign activation and analytics teams, ensuring data remains accurate, timely, and fit for purpose.
• Manage multiple concurrent initiatives, including modernization efforts and ongoing enhancement requests, while maintaining platform stability and data quality.
• Configure Azure Data Factory pipelines to orchestrate Databricks notebooks and Fabric-related processes as applicable.
• Use Azure DevOps for source control, versioning, and deployment of Azure Data Factory, Databricks, and Fabric assets.
• Test, monitor, and troubleshoot pipelines to ensure data reliability, performance, and quality.
• Collaborate with senior engineers, project managers, campaign services, analytics, and platform teams to deliver ongoing data solutions. Participate in the adoption and use of Microsoft Fabric, understanding how Fabric components (e.g., OneLake, Lakehouse, Warehousing) integrate with existing Azure and Databricks workflows.
• Maintain technical documentation for data pipelines, transformations, and datasets

Customer Success Manager

• Reporting to the Senior Director, Customer Success, you will be involved in all aspects of the internal/client support function for Anteriad.
• Internal and external client-facing resource available for Q and A on all details related to accounts.
• The ideal candidate will become the primary resource in this area for our customers, Sales Directors, and Operations team.
• Work in tandem with our India and US Operations teams in order to ensure Anteriad can offer true customer support and customer insights.
• Identify and escalate situations requiring urgent attention.
• Situations requiring escalation could arise from both customer and internal inquiries at any stage of a potential, active, or completed campaign.
• Collaborate with sales to develop strategies to help customers see greater success with Anteriad and grow their investments.
• Expert utilization and understanding of Salesforce and Qlik, as well as proprietary platforms to execute daily work.
• Be responsible for all products sold within their team for both non enterprise and enterprise customers.
• Understand customer motivations and use that understanding to improve their service campaign over campaign and quarter over quarter.
• Execute and present a wide range of reports including check-ins, campaign summaries, and QBRs.
• Assist Customer Success, Sales, Marketing, Operations, and Anteriad Management teams in any support and projects as needed.
• Utilize SFDC cases to track campaign status and offer pre-sales support activities.

Marketing

• Frame the problem. Translate ambiguous business questions ("why is performance down YoY?") into structured analyses with a clear hypothesis and a clear answer.
• Run the analysis. Pull and shape the data in SQL, build the models or tests, and pressure-test your own work before anyone else sees it.
• Tell the story. Turn statistical output into a narrative that our clients can act on.
• Be a trusted partner. Build relationships with client stakeholders so that when something complex comes up, you're the first call.
• Raise the bar. Bring better methods, sharper questions, and reusable frameworks back to the team.
• You will be expected to operate independently, prioritize effectively, and bring strategic thinking to every engagement. The ideal candidate is both technically strong and client-centric.
• Curiosity, accountability, and intellectual rigor are essential. You should naturally ask “why?” and “what does this mean for the business?”.

Data Engineer

Data Engineer

Customer Success Manager

Marketing Insights Lead