Lead Data Engineer @ Allata

Data & Analytics (1)

Allata is a global consulting and technology services firm with offices in the US, India, and Argentina. We help organizations accelerate growth, drive innovation, and solve complex challenges by combining strategy, design, and advanced technology. Our expertise covers defining business vision, optimizing processes, and creating engaging digital experiences. We architect and modernize secure, scalable solutions using cloud platforms and top engineering practices.

Allata also empowers clients to unlock data value through analytics and visualization and leverages artificial intelligence to automate processes and enhance decision-making. Our agile, cross-functional teams work closely with clients, either integrating with their teams or providing independent guidance—to deliver measurable results and build lasting partnerships.

We are seeking a skilled Lead Data Engineer to contribute to transformative enterprise data platform projects focused on developing data pipelines and logic engines to manage ingest, staging, and multi-tier data product modeling. Additionally, this includes but is not limited to data enrichment using various OEM-specific data warehouse and data lake house platform implementations for consumption via analytics clients. This role requires full life cycle design, build, deployment and optimization data products for multiple large enterprise industry vertical-specific implementations by processing datasets through a defined series of logically conformed layers, models, and views.

Role & Responsibilities:

Design and implement data pipelines using Microsoft Fabric’s integrated tools (Data Factory, Pipelines, Dataflows Gen2, etc.).
Work with Lakehouses and Delta tables to support structured and semi-structured data storage.
Develop and maintain data models and transformations using Fabric’s SQL and Spark engines.
Enable real-time and batch data processing for analytics and reporting use cases.
Collaborate with analysts, data scientists, and business users to understand data needs and deliver reliable, governed data products.
Ensure data quality, lineage, and compliance with security and governance policies.
Monitor and optimize performance and cost of data workflows.

Hard Skills - Must Have:

Experience in data engineering, with at least 1 year working directly with Microsoft Fabric (or deep experience in Synapse + Data Factory + Power BI prior to Fabric).
Proficiency in data modeling, ETL/ELT, and working with large-scale datasets.
Experience with Delta Lake and Lakehouse architectures.
Strong skills in SQL, and optionally in PySpark or T-SQL.
Familiarity with Microsoft Purview, Azure Data Lake, and Azure Active Directory integration.
Experience integrating data from various sources (on-prem, cloud, APIs).

Soft Skills / Business Specific Skills:

Ability to identify, troubleshoot, and resolve complex data issues effectively.
Strong teamwork, communication skills and intellectual curiosity to work collaboratively and effectively with cross-functional teams.
Commitment to delivering high-quality, accurate, and reliable data products solutions.
Willingness to embrace new tools, technologies, and methodologies.
Innovative thinker with a proactive approach to overcoming challenges.

At Allata, we value differences.

Allata is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Allata makes employment decisions without regard to race, color, creed, religion, age, ancestry, national origin, veteran status, sex, sexual orientation, gender, gender identity, gender expression, marital status, disability or any other legally protected category.

This policy applies to all terms and conditions of employment, including but not limited to, recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Lead Data Engineer

Fabric

Allata

Role & Responsibilities:

Hard Skills - Must Have:

Soft Skills / Business Specific Skills:

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