Data Engineer
Anteriad
| Company | Anteriad |
| Category | Engineering |
| Location | Remote-India |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 4 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Come Join Our Team At Anteriad and innovate the way B2B marketers make data-driven business decisions. 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