Lingaro

Turns data into AI-driven business insights

Data Engineering Architect

Data EngineeringConfirmed live in the last 24 hours

Part-timeRemote in IndiaNo salary listed

About the Job

Requirements

9–12 years of work experience as a Data Engineering Architect or in a similar role, with strong experience in Data & Analytics.
Proven experience using Microsoft ETL tools, including Azure Databricks, Azure Data Factory, Data Lake, and SQL Server Integration Services (SSIS), as well as Databricks, Unity Catalog, Asset Bundles, Microsoft Fabric, Logic Apps, and Function Apps.
Strong understanding of data engineering concepts, including data modeling, extract, transform, and load (ETL) processes, data pipelines, and data governance.
Expertise in designing and implementing scalable and efficient data processing frameworks.
In-depth knowledge of relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks such as Hadoop and Spark.
Experience selecting and integrating technologies to meet business requirements and long-term data strategy.
Ability to work closely with stakeholders to understand business needs and translate them into data engineering solutions.
Strong analytical and problem-solving skills to identify and address complex data engineering challenges.
Proficiency in Python, PySpark, and SQL.
Hands-on experience with Azure cloud platforms and designing and implementing data solutions in a cloud environment.
Knowledge of data governance principles and best practices, including data privacy and security regulations.
Experience leading and mentoring data engineering teams and providing technical guidance.
Familiarity with agile methodologies and experience working in agile development environments.
Strong project management skills, including prioritizing tasks, managing timelines, and delivering results within designated deadlines.
Strong understanding of distributed computing principles, including parallel processing, data partitioning, and fault tolerance.
Bachelor's degree in Computer Science, Information Technology, or a related field.

Responsibilities

Collaborate with stakeholders to understand business requirements and translate them into solutions. The source sentence is truncated after “translate them int”.
Collaborate with data scientists, analysts, and other stakeholders to define data requirements and enable effective data analysis and reporting.
Provide technical guidance and expertise to data engineering teams, promote best practices, ensure high-quality deliverables, and support the team throughout implementation by answering questions and addressing issues.
Oversee solution implementation to ensure it follows design documents and technical specifications.
Stay current with emerging data engineering trends and technologies, and recommend and implement innovative solutions as appropriate.
Analyze and optimize data engineering system performance by identifying and resolving bottlenecks and inefficiencies.
Ensure data quality and integrity across data engineering processes by implementing validation and monitoring mechanisms.
Collaborate with cross-functional teams to integrate data engineering solutions with other systems and applications.
Participate in project planning and estimation, providing technical insights and recommendations.
Document data architecture, infrastructure, and design decisions, keeping documentation current for implementation, reference, and knowledge sharing.

Desired Qualifications

A master's degree may be preferred.

Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics.

Freelance Cooperation – What Does It Mean?

Open-ended freelance agreement. An active sole proprietorship (B2B) is required throughout the duration of the agreement.
Part-time engagement. Work up to 50% of full-time workload, depending on current project needs.
Flexibility that fits your schedule. We’ll reach out whenever a suitable project opportunity comes up. If you’re available and interested, you can choose to join the project. If the timing isn’t right, you’re always free to decline without terminating the agreement.
No need to worry about the equipment. Freelancers typically work using equipment provided by us. Depending on the project, you may receive access to a virtual machine instead.

Tasks:

Collaborate with stakeholders to understand business requirements and translate them int

Collaborate with data scientists, analysts, and other stakeholders to define data requirements and enable effective data analysis and reporting.

Provide technical guidance and expertise to data engineering teams, promoting best practices and ensuring high-quality deliverables. Support to team throughout the implementation process, answering questions and addressing issues as they arise.

Oversee the implementation of the solution, ensuring that it is implemented according to the design documents and technical specifications.

Stay updated with emerging trends and technologies in data engineering, recommending and implementing innovative solutions as appropriate.

Conduct performance analysis and optimization of data engineering systems, identifying and resolving bottlenecks and inefficiencies.

Ensure data quality and integrity throughout the data engineering processes, implementing appropriate validation and monitoring mechanisms.

Collaborate with cross-functional teams to integrate data engineering solutions with other systems and applications.

Participate in project planning and estimation, providing technical insights and recommendations.

Document data architecture, infrastructure, and design decisions, ensuring clear and up-to-date documentation for implementation, reference and knowledge sharing.

What we are looking for:

9-12 year’s of work experience as a Data Engineering Architect or a similar role and strong experience in in the Data & Analytics area.

Proven experience in using of Microsoft ETL tools (Azure Databricks, Azure Data Factory, Data Lake and SSIS), Databricks, Unity Catalog, Asset Bundles, Data Factory, Microsoft Fabric. Logic App, Function App.

Strong understanding of data engineering concepts, including data modeling, ETL processes, data pipelines, and data governance.

Expertise in designing and implementing scalable and efficient data processing frameworks.

In-depth knowledge of various data technologies and tools, such as relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks (e.g., Hadoop, Spark).

Experience in selecting and integrating appropriate technologies to meet business requirements and long-term data strategy.

Ability to work closely with stakeholders to understand business needs and translate them into data engineering solutions.

Strong analytical and problem-solving skills, with the ability to identify and address complex data engineering challenges.

Proficiency in Python, PySpark, SQL.

Hands on experience with Azure cloud platforms, and experience in designing and implementing data solutions in a cloud environment.

Knowledge of data governance principles and best practices, including data privacy and security regulations.

Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.

Experience in leading and mentoring data engineering teams, providing guidance and technical expertise.

Familiarity with agile methodologies and experience in working in agile development environments.

Continuous learning mindset, staying updated with the latest advancements and trends in data engineering and related technologies.

Strong project management skills, with the ability to prioritize tasks, manage timelines, and deliver high-quality results within designated deadlines.

Strong understanding of distributed computing principles, including parallel processing, data partitioning, and fault-tolerance.

Bachelor's degree in Computer Science, Information Technology, or a related field. A Master's degree may be preferred.

What we offer:

Established global technology partner. Lingaro has been operating since 2008 and brings together 1,600+ professionals across 7 global locations.

Flexible collaboration model and working hours. Enjoy working from inspiring locations in line with our remote work policy.

A diverse, inclusive, and values-driven community.

Autonomy to choose the way you work. We trust your ideas.

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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