We are a multinational team of individuals who believe that, with the right knowledge and approach, technology is the answer to the challenges businesses face today. Since 2016, we have brought this knowledge and approach to our clients, helping them translate technology into their success.

With Swiss roots and our own development team in Lima and across the region, we offer the best of both cultures: the talent and passion of Latin American professionals combined with the organizational skills and Swiss mindset.

We are seeking a highly skilled Lead Data Engineer with strong expertise in PySpark, SQL, and Python, Azure Data Factory, Synapse, Databricks and Fabric, as well as a solid understanding of ETL and data warehousing end to end principles. The ideal candidate will have a proven track record of designing, building, and maintaining scalable data pipelines in a collaborative and fast-paced environment.

Key Responsibilities:

Design and develop scalable data pipelines using PySpark to support analytics and reporting needs.
Write efficient SQL and Python code to transform, cleanse, and optimize large datasets.
Collaborate with machine learning engineers, product managers, and developers to understand data requirements and deliver solutions.
Implement and maintain robust ETL processes to integrate structured and semi-structured data from various sources.
Ensure data quality, integrity, and reliability across pipelines and systems.
Participate in code reviews, troubleshooting, and performance tuning.
Work independently and proactively to identify and resolve data-related issues.
Contribute to Azure-based data solutions, including ADF, Synapse, ADLS, and other services.
Support cloud migration initiatives and DevOps practices.
Provide guidance on best practices and mentor junior team members when needed.

8+ years of overall experience working with cross-functional teams (machine learning engineers, developers, product managers, analytics teams).
3+ years of hands-on experience developing and managing data pipelines using PySpark.
3 to 5 years of experience with Azure-native services, including Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Databricks, Azure Synapse Analytics / Azure SQL DB / Fabric.
Strong programming skills in Python and SQL.
Solid experience doing ETL processes and data modeling/data warehousing end to end solutions.
Self-driven, resourceful, and comfortable working in dynamic, fast-paced environments.
Advanced written and spoken English is a must have for this position (B2, C1 or C2 only).
Strong communication skills is a must.

Nice to have:

Databricks certification.
Knowledge of DevOps, CI/CD pipelines, and cloud migration best practices.
Familiarity with Event Hub, IoT Hub, Azure Stream Analytics, Azure Analysis Services, and Cosmos DB.
Basic understanding of SAP HANA.
Intermediate-level experience with Power BI.

Please note that we will not be moving forward with any applicants who do not meet the following mandatory requirements:

3+ years of experience with PySpark/Python, ETL and data warehousing processes, Azure data factory, Synapse, Databricks, Azure Data Lake Storage, Fabric, Azure SQL DB etc.
Proven leadership experience in a current project or previous projects/work experiences.
Advanced written and spoken English fluency is a MUST HAVE (from B2 level to C1/C2)
MUST BE located in Central or South america, as this is a nearshore position (Please note that we are not able to consider candidates requiring relocation or those located offshore).

More Details:

Contract type: Independent contractor (This contract does not include PTO, tax deductions, or insurance. It only covers the monthly payment based on hours worked).
Location: The client is based in the United States; however, the position is 100% remote for nearshore candidates located in Central or South America.
Contract/project duration: Initially 6 months, with extension possibility based on performance.
Time zone and working hours: Full-time, Monday to Friday (8 hours per day, 40 hours per week), from 8:00 AM to 5:00 PM PST (U.S. time zone).
Equipment: Contractors are required to use their own laptop/PC.
Start date expectation: As soon as possible.
Payment methods: International bank transfer, PayPal, Wise, Payoneer, etc.

Bertoni Process Steps:

Requirements verification video interview.

Partner/Client Process Steps:

CV review.
1 Technical video interview with our partner.
1 or 2 video interviews with the end client.

Why Join Us?

Be part of an innovative team shaping the future of technology.
Work in a collaborative and inclusive environment.
Opportunities for professional development and career growth.

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