Lingaro

Turns data into AI-driven business insights

Azure Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeRemote in MexicoNo salary listedRemote

About the Job

Requirements

Four to six years of professional experience in a similar role.
Working experience with agile methodologies and supporting tools such as JIRA and Azure DevOps.
Hands-on experience designing and optimizing data storage, including data lakes, data warehouses, and distributed file systems.
Ability to work with Databricks, Apache Spark, data programming, software development for data engineering, Azure services, data-processing architecture, generative AI for data engineering, and CI/CD automation.
Familiarity with other cloud technologies, data warehouses, data governance, and business analysis is a plus.
Ability to deliver solutions independently and work under agile methodologies.
Ability to communicate clearly with co-workers and business stakeholders.

Responsibilities

Build data pipelines to ingest data from databases, APIs, and streaming platforms.
Integrate and transform data to ensure compatibility with target data models or formats.
Design and optimize data storage architectures, including data lakes, data warehouses, and distributed file systems; use partitioning, compression, and indexing to improve storage and retrieval.
Identify and resolve bottlenecks, tune queries, and implement caching strategies to improve retrieval speed and system efficiency.
Design and implement data models that support efficient storage, retrieval, and analysis.
Collaborate with data scientists and analysts to understand requirements and provide structured, optimized data for analysis and modeling.
Collaborate with cross-functional teams and business stakeholders to understand requirements and provide technical solutions.
Communicate technical concepts clearly to non-technical stakeholders.
Design and implement data processing systems on Azure, writing scalable code to process, transform, and clean structured and unstructured data.
Train and mentor junior data engineers, providing guidance and knowledge transfer.

Desired Qualifications

Familiarity with other cloud technologies, data warehouses, data governance, and business analysis.

Building data pipelines to ingest data from various sources such as databases, APIs, or streaming platforms. Integrating and transforming data to ensure its compatibility with the target data model or format
Designing and optimizing data storage architectures, including data lakes, data warehouses, or distributed file systems. Implementing techniques like partitioning, compression, or indexing to optimize data storage and retrieval. Identifying and resolving bottlenecks, tuning queries, and implementing caching strategies to enhance data retrieval speed and overall system efficiency.
Designing and implementing data models that support efficient data storage, retrieval, and analysis. Collaborating with data scientists and analysts to understand their requirements and provide them with well-structured and optimized data for analysis and modeling purposes.
Collaborating with cross-functional teams including data scientists, analysts, and business stakeholders to understand their requirements and provide technical solutions. Communicating complex technical concepts to non-technical stakeholders in a clear and concise manner.
Independence and responsibility for delivering a solution
Ability to work under Agile and Scrum development methodologies
Train and mentor junior data engineers, providing guidance and knowledge transfer
Designing and implementing data processing systems on Azure platform. This involves writing efficient and scalable code to process, transform, and clean large volumes of structured and unstructured data.
Building data pipelines to ingest data from various sources such as databases, APIs, or streaming platforms.
Integrating and transforming data to ensure its compatibility with the target data model or format.
Identifying and resolving bottlenecks, tuning queries, and implementing caching strategies to enhance data retrieval speed and overall system efficiency.
Collaborating with cross-functional teams including data scientists, analysts, and business stakeholders to understand their requirements and provide technical solutions.

What We're Looking For:

Databricks 4/5.
Apache Spark 4/5.
Programming – Data 4/5.
Software Development for DE – 4/5.
Azure Services – 3/5.
Technical Leadership – 3/5.
Architecture – Data Processing – 3/5.
GenAI for Data Engineering – 3/5.
CI/CD Automation 3/5.

Other:
4-6 years of professional experience in a similar role.
Very good level of communication including ability to convey information clearly and specifically to co-workers and business stakeholders.
Working experience in the agile methodologies – supporting tools (JIRA, Azure DevOps).
Experience or familiarity with other cloud technologies, data warehouses, data governance, and business analysis is a plus.
Independence and responsibility in delivering solutions.
Ability to work under agile methodologies.
Hands-on experience in designing and optimizing of data storage (data lakes, data warehouses, distributed file systems).

About the Company

Lingaro

Turns data into AI-driven business insights

Lingaro helps large organizations turn data into business value. It provides end-to-end data and AI services, from strategy and advisory to building scalable data platforms and AI solutions. Its team turns complex data into actionable insights, advanced analytics, and AI-driven automation, enabling faster decisions and greater efficiency. Lingaro distinguishes itself with global reach rooted in Europe, strong engineering expertise, agility, and deep industry knowledge, serving 75+ brands in 30+ countries, including highly regulated sectors. As a long-term transformation partner, the company aims to make organizations data-ready, AI-ready, and future-ready, delivering measurable business impact across teams and processes.

Company size: 1,001-5,000
Company stage: Not listed
Total funding: Not listed
Headquarters: Warsaw, Poland
Founded: 2008

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