Lingaro

Turns data into AI-driven business insights

GCP Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Part-timeRemote in IndiaNo salary listed

About the Job

Requirements

At least 8–10 years of experience as a Data Engineer, including 6+ years working with GCP cloud-based infrastructure and systems.
Deep knowledge of Google Cloud Platform and cloud computing services.
Extensive experience designing, building, and deploying cloud data pipelines that ingest data from databases, APIs, or streaming platforms.
Proficiency in database management systems, including SQL and NoSQL; BigQuery is required. Ability to design, configure, and manage databases for optimal performance and reliability.
Programming skills in SQL, Python, or other scripting languages.
Proficiency in data modeling techniques and database optimization, including query optimization, indexing, and performance tuning.
Knowledge of at least one orchestration and scheduling tool; Airflow is required.
Experience with data integration techniques such as ETL and ELT, integrating data from multiple sources and transforming it for analysis.
Knowledge of modern data transformation tools such as dbt or Dataform.
Ability to participate in or lead client discussions to identify and assess improvement opportunities.
Knowledge of tools such as Git, Jira, and Confluence.
Experience in a multinational environment and with distributed teams.
An active sole proprietorship (B2B) is required throughout the agreement.

Responsibilities

Design, model, and develop a client's GCP data ecosystem, including Cloud Storage, Cloud Functions, and BigQuery.
Gather, analyze, model, and document business and technical requirements, including direct contact with clients.
Model data from various sources and technologies; troubleshoot and support complex, high-impact problems; and deliver new features and functionalities.
Design and optimize data storage architectures, including data lakes, data warehouses, and distributed file systems.
Implement partitioning, compression, and indexing to optimize storage and retrieval.
Identify and resolve bottlenecks, tune queries, and implement caching strategies to improve data retrieval speed and system efficiency.
Identify and resolve issues in data processing, storage, or infrastructure; monitor system performance, identify anomalies, and conduct root cause analysis to maintain data operations.
Train and mentor less experienced data engineers, providing guidance and knowledge transfer.

Desired Qualifications

Certifications in big data technologies or cloud platforms.
Experience with business intelligence solutions such as Looker, Power BI, or Tableau.
Experience with ETL tools such as Talend or Alteryx.
Experience with Apache Spark, especially in a GCP environment.
Experience with Databricks.
Experience with Azure cloud-based infrastructure and systems.
Ability to learn new technologies and solutions.

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:

You will be a part of the team accountable for design, model and development of whole GCP data ecosystem for one of our Client’s (Cloud Storage, Cloud Functions, BigQuery).
Involvement throughout the whole process starting with the gathering, analyzing, modelling, and documenting business/technical requirements will be needed. The role will include direct contact with clients.
Modelling the data from various sources and technologies. Troubleshooting and supporting the most complex and high impact problems, to deliver new features and functionalities.
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.
Identifying and resolving issues related to data processing, storage, or infrastructure. Monitoring system performance, identifying anomalies, and conducting root cause analysis to ensure smooth and uninterrupted data operations.
Train and mentor less experienced data engineers, providing guidance and knowledge transfer.

What We're Looking For:

At least 8-10 years of experience as a Data Engineer working with 6+ years in GCP cloud-based infrastructure & systems.
Deep knowledge of Google Cloud Platform and cloud computing services.
Extensive experience in design, build, and deploy data pipelines in the cloud, to ingest data from various sources like databases, APIs or streaming platforms.
Proficient in database management systems such as SQL (Big Query is a must), NoSQL. Candidate should be able to design, configure, and manage databases to ensure optimal performance and reliability.
Programming skills (SQL, Python, other scripting).
Proficient in data modeling techniques and database optimization. Knowledge of query optimization, indexing, and performance tuning is necessary for efficient data retrieval and processing.
Knowledge of at least one orchestration and scheduling tool (Airflow is a must).
Experience with data integration tools and techniques, such as ETL and ELT Candidate should be able to integrate data from multiple sources and transform it into a format that is suitable for analysis.
Knowledge of modern data transformation tools (such as DBT, Dataform).
Excellent communication skills to effectively collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders. Ability to convey technical concepts to non-technical stakeholders in a clear and concise manner.
Ability to actively participate/lead discussions with clients to identify and assess concrete and ambitious avenues for improvement.
Tools knowledge: Git, Jira, Confluence, etc.
Open to learn new technologies and solutions.
Experience in multinational environment and distributed teams.

Good to have:

Certifications in big data technologies or/and cloud platforms.
Experience with BI solutions (e.g. Looker, Power BI, Tableau).
Experience with ETL tools: e.g. Talend, Alteryx
Experience with Apache Spark, especially in GCP environment.
Experience with Databricks.
Experience with Azure cloud-based infrastructure & systems.

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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