Lead Data Engineer - 100% remote Job.

Remote Full-time
Company Description

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.

Job Description

We are currently looking for a Lead Data Engineer to join our external team in a full-time, 100% remote role (outsourcing model, with the hiring process and engagement managed by Bertoni Solutions) to work with one of our U.S.-based clients.

Qualifications

Must Have: PySpark
Strong in SQL, Python / PySpark , ETL and data warehousing fundamentals.

Must have Skills :
8+ Years of total experience collaborating with cross-functional teams, including machine learning engineers, software developers, analytics engineers, and product managers to translate business requirements into highly available data solutions
3+ years of experience developing and implementing data pipelines using PySpark.
Proven experience with SQL
Be an independent self-learner with the “let’s get this done” approach and ability to work in Fast paced and Dynamic environment
Advanced written and Spoken English (B2 or C1/C2).
Good-to-Have Skills:
Good to have Databricks Certification
Good to have Experience providing practical direction within azure native services , implementing data migration and data processing using Azure services: ADLS, Azure Data Factory, Synapse/DW /Azure SQL DB, Fabric.
Good to have Event Hub, IOT Hub, Azure Stream Analytics, Azure Analysis Service, Cosmo Db knowledge.
Good to have SAP Hana knowledge
Intermediate knowledge on Power BI
Good to have knowledge in DevOps and CI/CD deployments, Cloud migration methodologies and processes

Additional Information

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


8+ Years of total experience collaborating with cross-functional teams, including machine learning engineers, software developers, analytics engineers, and product managers to translate business requirements into highly available data solutions
3+ years of experience developing and implementing data pipelines using PySpark/Python.
Proven experience with SQL
ETL Experience and data warehousing fundamentals.
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 (no paid holidays or vacation, tax deductions, or insurance). Compensation is based on gross monthly payment for hours worked.
Location: 100% remote; client is based in the U.S.
Contract Duration: 1-year, renewable annually based on performance.
Schedule: Monday to Friday, 8 AM to 5 PM PST (full-time, 40 hrs/week).
Equipment: You must use your own laptop or PC.
Start Date: As soon as possible.
Onboarding process: Onboarding begins after candidate selection and includes an in-person identity verification due to the end client’s security requirements. Candidates located near cities with representatives are prioritized; otherwise, they will need to travel for verification (expenses reimbursed by Bertoni after the first month).

Bertoni Process Steps:
Requirements verification video interview.

Partner/Client Process Steps:
CV review.
1 Technical video interview with our partner.
1 Interview with the final 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.

Compensation: up to USD 30 - hourly
Apply Now →

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