Lingaro

Turns data into AI-driven business insights

Azure Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Part-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

An active sole proprietorship (B2B) is required throughout the agreement.
A Bachelor's or master's degree in Computer Science, Information Systems, or a related field is typically required.
At least 8 years of experience in data engineering or a related field.
Proficiency in Python, SQL, and PySpark.
Familiarity with Azure cloud, including Azure Databricks, Azure Data Factory, and Azure Data Lake, and experience implementing cloud data solutions.
Expertise with ETL frameworks, data pipelines, and data warehousing solutions.
In-depth knowledge of data management principles, including data governance, data quality, and data integration.
Knowledge of data security and privacy regulations and ability to ensure compliance in data engineering projects.
Must-have skills include Databricks, Python, SQL query writing, Delta Lake, data lake concepts, data warehousing, Azure Data Factory, Azure Synapse, Spark architecture, data governance, and Azure DevOps.

Responsibilities

Provide technical expertise and direction in data engineering, guide the team in selecting tools, technologies, and methodologies, stay current with advancements, and ensure best practices and industry standards are followed.
Collaborate with stakeholders to understand project requirements, define scope, and create project plans.
Support project managers in delivering projects on schedule, within budget, and to quality standards; monitor progress, identify risks, and implement mitigation strategies.
Oversee data solution design and architecture with data architects and stakeholders; ensure solutions are scalable, efficient, and aligned with business requirements; guide data modeling, database design, and data integration.
Align coding standards and conduct code reviews to ensure code quality.
Identify and introduce quality assurance processes for data pipelines and workflows.
Optimize data processing and storage for performance, efficiency, and cost savings.
Evaluate and implement technologies to improve data engineering processes, including continuous integration and continuous delivery, quality assurance, and coding standards.
Maintain project technical documentation, control its validity, and review it regularly.
Ensure compliance with security standards and regulations.

Desired Qualifications

Additional cloud certifications are advantageous.
Consulting exposure and an external customer-focused mindset are 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.

Task:

Provide technical expertise and direction in data engineering, guiding the team in selecting appropriate tools, technologies, and methodologies. Stay updated with the latest advancements in data engineering and ensure the team follows best practices and industry standards. 
Collaborate with stakeholders to understand project requirements, define scope, and create project plans. 
Support project managers to ensure that projects are executed effectively, meeting timelines, budgets, and quality standards. Monitor progress, identify risks, and implement mitigation strategies.  
Oversee the design and architecture of data solutions, collaborating with data architects and other stakeholders. Ensure data solutions are scalable, efficient, and aligned with business requirements. Provide guidance in areas such as data modeling, database design, and data integration. 
Align coding standards, conduct code reviews to ensure proper code quality level. 
Identify and introduce quality assurance processes for data pipelines and workflows. 
Optimize data processing and storage for performance, efficiency and cost savings. 
Evaluate and implement new technologies to improve data engineering processes on various aspects (CICD, Quality Assurance, Coding standards). 
Maintain technical documentation of the project, control validity and perform regular reviews of it. 
Ensure compliance with security standards and regulations.

What we are looking for:

A Bachelor's or master's degree in computer science, Information Systems, or a related field is typically required. Additional certifications in cloud are advantageous. 
Minimum of 8-10 years of experience in data engineering or a related field. 
Strong technical skills in data engineering, including proficiency in programming languages such as Python, SQL, Pyspark.
Familiarity with Azure cloud platform viz. Azure Databricks, Data Factory, Data Lake etc., and experience in implementing data solutions in a cloud environment. 
Expertise in working with various data tools and technologies, such as ETL  frameworks, data pipelines, and data warehousing solutions. 
In-depth knowledge of data management principles and best practices, including data governance, data quality, and data integration. 
Excellent problem-solving and analytical skills, with the ability to identify and resolve complex data engineering issues. 
Knowledge of data security and privacy regulations, and the ability to ensure compliance within data engineering projects. 
Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams, stakeholders, and senior management. 
Continuous learning mindset, staying updated with the latest advancements and trends in data engineering and related technologies. 
Consulting exposure, with external customer focus mindset is preferred.

Must have skills: Databricks, Python, writing SQL queries, Delta lake, Data Lake concept, DWH, ADF, Azure Synapse, spark architecture, Data Governance, Azure Devops.

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.

Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.

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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