Job SummaryLead Data Engineer Role As a Lead Data Engineer, you will:

- Lead the design, development, and evolution of enterprise-grade data platforms and pipelines supporting credit risk products, decisioning capabilities, and analytics solutions.
- Architect and implement scalable ETL/ELT frameworks utilizing Databricks, Spark, Delta Lake, and cloud-native technologies.
- Establish data quality, lineage, governance, observability, and monitoring capabilities to ensure trusted and compliant data products.
- Drive the migration and modernization of legacy data assets into cloud-based architectures and Data Lakehouse platforms.
- Partner with Risk, Product, Architecture, and Engineering teams to translate business requirements into scalable technical solutions.
- Define and promote engineering standards, coding practices, testing frameworks, Data Quality frameworks, deployment automation, and operational excellence across the data ecosystem.
- Lead technical design reviews and influence architectural direction for data-intensive applications and services.
- Optimize large-scale data processing workloads for performance, reliability, scalability, and cost efficiency.
- Enable AI and advanced analytics initiatives through creation of high-quality, reusable, governed data products.
- Mentor, coach, and raise the technical capability of engineers across the organization by fostering a culture of ownership, continuous learning, accountability, and engineering excellence.
- Shape strategic roadmap planning, technology evaluation, and delivery priorities across the ECR portfolio, balancing business outcomes, engineering feasibility, risk, compliance, and long-term platform sustainability.
- Support regulatory, compliance, security, and audit requirements through robust engineering controls and documentation.




- Own complex problems with dependencies across multiple services and facilitate cross-functional collaboration to drive resolution.
- Conduct technical interviews, assess engineering talent, and contribute to raising the overall performance bar of the organization.

All About You The idóneo candidate for this position should have:

Essential Skills & Experience

- Strong expertise in designing and implementing large-scale data engineering solutions and distributed data processing systems.
- Advanced proficiency with Databricks, Apache Spark, Delta Lake, SQL, Hadoop, and Python.
- Experience building and operating cloud-based data platforms on Azure, AWS, or GCP.
- Expertise developing enterprise-grade ETL/ELT pipelines, streaming architectures, and data integration frameworks.
- Strong understanding of data modeling techniques for analytical and operational workloads.
- Experience implementing data quality frameworks, lineage, metadata management, and governance practices.
- Experience with Data formats (Parquet, Avro, ORC).
- Working knowledge of CI/CD pipelines, infrastructure-as-code, automated testing, and DevOps practices.
- Experience with Workflow orchestration Tools like Airflow.
- Strong understanding of security, privacy, and compliance requirements associated with sensitive financial and customer data.
- Proven ability to lead technical initiatives across multiple teams and influence engineering direction without direct authority.
- Excellent communication skills with the ability to collaborate effectively across technical and business functions.




- Demonstrated leadership in aligning engineering teams around shared goals, driving delivery through ambiguity, and creating clarity for stakeholders across product, risk, analytics, architecture, and operations.
- Ability to influence senior technical and business stakeholders, make thoughtful trade-off decisions, and guide teams toward pragmatic solutions that improve credit risk outcomes and operational resilience.
- Knowledge of Java Based application development is a huge Plus.

Leadership Skills

- Lead by influence across engineering, product, risk, analytics, and architecture teams to align priorities and deliver measurable business outcomes.
- Create clarity in complex, ambiguous environments by translating business needs into actionable technical direction and execution plans.
- Develop engineering talent through mentoring, knowledge sharing, design guidance, and constructive feedback.
- Promote a high-accountability culture focused on quality, reliability, security, compliance, and continuous improvement.
- Communicate effectively with senior stakeholders and clearly articulate trade-offs, risks, dependencies, and delivery progress.

Preferred Qualifications

- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related STEM discipline or alternative minimum of 10 years of experience in a related field.

Technical Skills Preferred expertise in:

- Databricks
- Apache Spark / PySpark
- Hadoop
- AirFlow
- Delta Lake
- SQL
- Python
- Azure Data Services
- Kafka/Event Streaming
- GitHub / CI-CD Tooling

Locations

- Skill Set: SQL, Python, Kafka, Azure, Spark, Databricks, Airflow, Hadoop ETL, Delta Lake
- Total Experience: 7.00 to 10.00 Years
- No of Openings: 1
- Job Post Date: 26/08/2026
- Job Expiry Date: 01/10/2026
- Domain: IT
- Location: GUADALAJARA [Mexico]
- Job Reference No: 4103892

📌 Tech Lead Data Engineer (based in MX) (México)
🏢 Tech Mahindra
📍 México