Data Engineer Azure

Softtek is a global company that helps organizations bridge the digital gap. With a presence in North America, Latin America, Europe, and Asia, Softtek provides Global 2000 organizations with technological solutions that create value through technology. We are looking for talent such as:

Proficient Azure Data Engineer (Hybrid Modality in CDMX)

Azure Data Factory (ADF)

• Minimum 3 years of experience working with Azure Data Factory.
• Development and administration of complex pipelines.
• Configuration of Linked Services, Datasets, Triggers, and Integration Runtime.
• Development of Mapping Data Flows.
• Implementation of incremental loads.
• Orchestration and automation of data integration processes.
• Integration of multiple on-premise and cloud data sources.
• Monitoring, troubleshooting, and optimization of production processes.

Azure Databricks

• Solid experience in Azure Databricks.
• Development of notebooks in Python and SQL.
• Apache Spark, PySpark, and Spark SQL.
• Distributed processing of large volumes of data.
• Optimization of processes and performance.
• Handling of Delta Lake.
• Design and implementation of Lakehouse architectures.
• Construction of data cleaning, transformation, and enrichment processes.

PostgreSQL

• Advanced SQL.
• Design and optimization of complex queries.
• Development of views, functions, and stored procedures.
• Design of relational databases.
• Indexing and performance tuning.
• Performance analysis and query optimization.
• Handling of large volumes of information.

Data Engineering and Architecture

• Design and implementation of ETL/ELT processes.
• Construction of data integration and transformation pipelines.
• Automation of loads and processing flows.
• Design of scalable and high-performance solutions.
• Analytical data modeling.
• Implementation of quality, traceability, and data governance standards.
• Experience in Data Warehouses and Data Lakes.

Desirable Skills:

• Azure Synapse Analytics.
• Azure Data Lake Storage (ADLS).
• Microsoft Fabric.
• Power BI.
• Apache Airflow.
• Snowflake.
• MongoDB.
• Azure DevOps.
• Git and GitHub.
• Implementation of CI/CD for data solutions.
• Terraform.
• Docker.
• Kubernetes.
• Data Governance.
• Data Quality Frameworks.
• Experience in modern data architectures and advanced analytics.

Responsibilities

Data Engineering Solutions Development

• Design and develop data integration and transformation pipelines.
• Implement ETL/ELT processes to consolidate information from multiple sources.
• Automate data loads and processing flows.
• Guarantee the quality, integrity, and traceability of information.
• Develop scalable solutions for processing large volumes of data.

Azure Data Factory

• Design, implement, and administer pipelines in Azure Data Factory.
• Configure Linked Services, Datasets, Data Flows, and Triggers.
• Implement incremental loads and orchestration processes.
• Monitor and optimize execution times and resource consumption.
• Manage integrations between cloud platforms and on-premise environments.
• Resolve incidents and operational problems related to data integrations.

Development in Databricks

• Build data transformation and enrichment processes using Databricks.
• Develop notebooks in Python, PySpark, and SQL.
• Implement solutions on Lakehouse and Delta Lake architectures.
• Optimize processes through Apache Spark and distributed processing.
• Collaborate on advanced analytics and data science initiatives.

PostgreSQL

• Design and optimize complex SQL queries.
• Create functions, views, and stored procedures.
• Execute database analysis and tuning.
• Guarantee data consistency and integrity.
• Participate in the logical and physical design of information models.

Data Governance and Modeling

• Design analytical data models and structures for Data Warehouse.
• Participate in Data Lake initiatives and enterprise analytical platforms.
• Apply data governance, security, and quality standards.
• Maintain updated technical documentation, catalogs, and data dictionaries.

Business Collaboration

• Gather requirements from functional users and business areas.
• Translate business needs into scalable technical solutions.
• Build metrics and indicators for operational and strategic analysis.
• Participate in architecture, design, and data solution definition sessions.

Required Languages

Low-Intermediate English

We Offer:

Statutory Benefits, Major Medical Expenses, Minor Medical Expenses, Life Insurance, accident and dental insurance, Savings Fund, Discount Card, English classes, courses and certifications, Sports and social responsibility activities, car insurance at approx. 50%, among other benefits.

-Requirements-

Minimum education: Higher education

• Bachelor's degree 3 years of experience

Age: between 27 and 55 years

Keywords: datos, data, ingeniero, engineers, ingeniera, ing, engineer