Senior Data Engineer
7 days ago
This is a remote position.
At Softgic we work with the coolest, with those who build, with those who love what they do, with those who have 100 in attitude, because that's our #Cooltura. Join our purpose of making life easier with technology and be part of our team as a Data Engineer.Compensation:
USD 20 - 28/hour.
Location:
Remote (Remote for México, Guatemala, Colombia, Perú, Chile, Argentina, Paraguay, Brasil, Honduras, Jamaica, República Dominicana, Belice, Estados Unidos, Panamá, Canadá, España, South Africa, Kenia, India, Filipinas residents).
Mission of Softgic:
In Softgic S.A.S. we work for the digital and cognitive transformation of our clients, aware that quality is an essential factor for us, we incorporate the following principles into our policy:
- Deliver quality products and services.
- Achieve the satisfaction of our internal and external clients.
- Encourage in our team the importance of training to grow professionally and personally through development plans.
- Comply with the applicable legal and regulatory requirements.
- Promote continuous improvement of the quality management system.
- You are expert in data architecture.
- You are proficient in Azure Data Lake, Databricks, ELT (Extract, load, transform), and ETL (Extract, transform, load).
- English - English - Native or fully fluent.
This vacancy is 100% On-site in: Colombia, Guatemala, Mexico, Peru, Chile, Belize, United States, Canada, Spain, Dominican Republic, Jamaica, Honduras, Brazil, Paraguay, Argentina, South Africa, Kenya, India, Philippines.
Job Responsibilities:
- Design, develop, and maintain scalable data architectures using SQL Server, Azure SQL Database, and Snowflake on Azure.
- Implement and manage data pipelines using Azure Data Factory, supporting ETL and ELT processes.
- Work with SQL Change Data Capture (CDC) along with Debezium to enable real-time and incremental data processing.
- Work with Streaming technologies such as Kafka and Azure Event Hub to deliver near real time analytics and reporting.
- Manage Azure Data Lake to store and process structured and unstructured data efficiently.
- Design and optimize Data Vault and Star Schema models for data warehousing solutions.
- Develop and maintain ETL/ELT workflows using Python and SQL-based tools.
- Leverage Databricks for big data processing, machine learning, and advanced analytics.
- Ensure data quality, governance, and security across multiple data environments.
- Build and maintain analytical reports using Sigma
- Collaborate with business stakeholders and data analysts to ensure data solutions align with business needs.
- Monitor and troubleshoot data pipelines to ensure reliability, accuracy, and efficiency.
- Support disaster recovery planning and high-availability data strategies.
- Stay up to date with emerging data engineering technologies and best practices.
Requirements Abilities:
- 5-7 years of experience as a data architect or senior-level data engineer.
- Expertise in SQL Server (SSMS, T-SQL, SSIS, SSRS, SSAS) and Azure SQL Database.
- Strong experience in data modeling, including Data Vault and Star Schema methodologies.
- Proficiency in ETL/ELT development and data pipeline management.
- Hands-on experience with Snowflake on Azure and Databricks for big data processing.
- Experience working with streaming technologies (e.g., Kafka, Flint, Event Hub)
- Strong analytical and problem-solving skills with a focus on data integrity and scalability.
- Knowledge of Python for data transformation, automation, and analytics is a bonus.
Requirements:
- Ability to sit or stand for extended periods of time as required.
- Ability to work in a fast-paced, deadline-driven environment with minimal supervision.
Benefits
- We're certified as a Great Place to Work.
- Opportunities for advancement and growth.
- Paid time off.
- Formal education and certifications support.
- Benefits with partner companies.
- Referral program.
- Flexible working hours.
Requirements
Abilities: 5-7 years of experience as a data architect or senior-level data engineer. Expertise in SQL Server (SSMS, T-SQL, SSIS, SSRS, SSAS) and Azure SQL Database. Strong experience in data modeling, including Data Vault and Star Schema methodologies. Proficiency in ETL/ELT development and data pipeline management. Hands-on experience with Snowflake on Azure and Databricks for big data processing. Experience working with streaming technologies (e.g., Kafka, Flint, Event Hub) Strong analytical and problem-solving skills with a focus on data integrity and scalability. Knowledge of Python for data transformation, automation, and analytics is a bonus. Requirements: Ability to sit or stand for extended periods of time as required. Ability to work in a fast-paced, deadline-driven environment with minimal supervision.
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