We are seeking a highly skilled Senior Data Engineer with strong experience in Databricks and Microsoft Azure to design, develop, and maintain scalable data solutions that support business intelligence, analytics, and operational workloads. This role is responsible for building robust data pipelines, optimizing data processing, and ensuring reliable, high-performance data platforms.
You will collaborate with clients, business stakeholders, and cross-functional engineering teams to translate business requirements into scalable technical solutions. This position also involves partnering with distributed teams globally, requiring strong communication and collaboration skills to deliver high-quality data solutions.
Responsibilities
Design, develop, and maintain scalable data pipelines using Databricks and Azure services.
Build and optimize ETL/ELT workflows to support data ingestion, transformation, and delivery.
Develop and optimize Apache Spark (PySpark) jobs to efficiently process large-scale datasets.
Design and implement scalable data solutions that support analytics, reporting, and operational business needs.
Collaborate with business stakeholders and clients to gather requirements and translate them into technical solutions.
Ensure data quality, consistency, reliability, and performance across all data processing workflows.
Optimize data processing jobs and storage solutions to improve performance and resource utilization.
Troubleshoot and resolve issues related to data pipelines, Spark jobs, and Azure data services.
Participate in architecture discussions, code reviews, and technical design sessions.
Create and maintain technical documentation for data pipelines, data models, and operational processes.
Work closely with distributed teams globally to coordinate delivery efforts and support effective cross-team collaboration.
5+ years of experience in data engineering or related roles.
Strong hands-on experience with Databricks for building and managing data pipelines.
Strong experience with Microsoft Azure and Azure-based data services.
Experience developing and optimizing Apache Spark (PySpark) applications.
Strong experience designing and implementing ETL/ELT data processing solutions.
Good understanding of data architecture, data modeling, and scalable data platform design.
Experience working with SQL for data transformation and analysis.
Experience building and maintaining distributed data processing solutions.
Strong analytical and problem-solving skills with attention to detail.
Excellent communication and collaboration skills, with experience working directly with clients and cross-functional teams.
Experience working effectively with distributed teams.
Experience working in Agile development environments.
Nice to Have
Experience working with Delta Lake and Lakehouse architectures.
Familiarity with data governance, monitoring, and data quality best practices.
Microsoft Azure or Databricks certifications.
Perks you enjoy at KMS Mexico
- Mexican law benefits
- 15 days of PTO (in year zero, from the first year onwards it is 3 days per year).
- 5 days' leave for the death of immediate family members, negotiable.
- Major Medical Expenses Insurance with coverage for immediate dependents (spouse and children).
- Annual performance bonus (≈10% of annualized salary).
- Annual salary adjustment.
- Employee Referral Bonus.
- Paid Certifications / Courses
- Coursera License.
- 5% Savings Fund.
- 5% Grocery Vouchers.