Senior Data Engineer

Blend360

Senior Data Engineer developing data solutions for high-impact enterprise initiatives at Blend. Focusing on data processing and building reliable data pipelines for analytics and business workflows.

Posted 7/18/2026full-timeRemote • 🇲🇽 MexicoSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing data ingestion architectures using Snowflake, with a strong focus on data quality, validation, and transformation. Proficient in SQL and Python for processing large datasets and collaborating with stakeholders to deliver scalable data solutions.

Highest-signal resume keywords

SnowflakePython Data ProcessingSQLData ValidationETL Pipeline Development

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Hard Skills

Data EngineeringData AnalyticsData TransformationData NormalizationData Quality AssuranceData Ingestion WorkflowsLarge-Scale DatasetsFile HandlingValidation RulesMonitoring Processes

Soft Skills

Attention to DetailEffective CommunicationCollaboration

Tools & Technologies

SalesforceTamaracCompassSharePoint

Tech Stack

Tools & technologies

ETLPythonSQL

About the role

Key responsibilities & impact

Design, develop, and maintain data pipelines to ingest, transform, and normalize data from multiple sources.
Lead the design and implementation of data ingestion architectures in Snowflake, ensuring scalability and reliability.
Apply best practices in data validation to ensure accuracy, consistency, and reliability across datasets.
Perform data transformation and normalization to support analytics and reporting use cases.
Work with large datasets using SQL and Python to process and analyze data efficiently.
Ensure data quality by implementing validation rules, checks, and monitoring processes.
Collaborate with business and technical stakeholders to understand data requirements and translate them into scalable solutions.
Support ETL processes and file handling workflows for structured and semi-structured data.
Contribute to documentation and continuous improvement of data processes and standards.

Requirements

What you’ll need

4+ years of experience in Data Engineering or Data Analytics roles with strong engineering focus.
Strong hands-on experience with Snowflake (Must).
Strong hands-on experience with Python for data processing and transformation.
Strong experience with SQL and working with large-scale datasets.
Proven experience in data validation, data transformation, and normalization.
Experience building and maintaining ETL pipelines and handling data ingestion workflows.
Strong attention to detail with a focus on data quality and reliability.
Ability to work in cross-functional environments and communicate effectively with stakeholders.
Nice to have: Experience working with Salesforce data structures.
Familiarity with Tamarac or similar RIA platforms.
Experience with Compass or SharePoint integrations.
Experience with file handling and ingestion processes (e.g., CSV, JSON, batch files).

Benefits

Comp & perks

Learning Opportunities: Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
Access to AI learning paths to stay up to date with the latest technologies.
Study plans, courses, and additional certifications tailored to your role.
Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
English lessons to support your professional communication.
Travel opportunities to attend industry conferences and meet clients.
Mentoring and Development: Career development plans and mentorship programs to help shape your path.
Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
Company-provided equipment.
Flexible working options to help you strike the right balance.
Other benefits may vary according to your location in LATAM.