Data Engineer (Azure) - Remote, Latin America

Software Development

Excel

WFA Digital Insight

As demand for skilled data engineers continues to surge, with some estimates showing a 25% increase in demand over the past year, professionals with expertise in cloud-based data engineering are highly sought after. Bluelight Consulting, a leader in innovative software solutions, is looking to expand its team with a talented Data Engineer specializing in Azure. This role stands out for its focus on collaborative work environments and continuous learning, making it an attractive opportunity for those who thrive in dynamic, team-oriented settings. Before applying, candidates should be prepared to showcase their proficiency in Python, Azure Synapse Analytics, and data warehousing concepts, as well as their ability to work closely with cross-functional teams.

Job Description

About the Role

The Data Engineer (Azure) position at Bluelight Consulting is a critical role that involves designing, developing, and maintaining data integration processes using Python (PySpark) and Azure Synapse Analytics. This role is integral to ensuring the accuracy and availability of analytical data for insights and decision-making. As part of a collaborative and diverse community, the successful candidate will work closely with data scientists, analysts, and other stakeholders to deliver high-quality data solutions.

The ideal candidate is a passionate software development professional who thrives in fast-paced, dynamic environments where everyone's opinions and efforts are valued. Bluelight Consulting is committed to fostering a work environment that promotes growth, learning, and personal development, making this an exciting opportunity for those looking to advance their careers in data engineering.

Bluelight Consulting is a leading software consultancy dedicated to designing and developing innovative technology that enhances users' lives. With a presence across the United States and Central/South America, the company is in an exciting phase of expansion, continually seeking exceptional talent to join its dynamic community.

What You Will Do

Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks and/or Azure Synapse Analytics Pipelines.
Apply expertise in data warehousing to design and build effective data storage structures in a Massively Parallel Processing (MPP) SQL Pool.
Extract data from various sources, including REST APIs, SQL database tables, and CSV files.
Utilize deep knowledge of Azure Synapse Analytics to design and optimize data notebooks/pipelines for scalability and performance.
Contribute to the implementation and understanding of Data Fabric concepts, such as data lakes, lakehouses, delta lakes, and data cataloging.
Collaborate with data architects to create data models and schemas that align with business requirements.
Implement data quality checks and validation processes to maintain data accuracy and consistency.
Identify and resolve performance bottlenecks and optimize ETL data notebooks/pipelines to meet SLAs.
Monitor ETL jobs, diagnose issues, and implement solutions to ensure data pipeline reliability.
Maintain comprehensive documentation of ETL data engineering processes, data flows, and data transformations.

What We Are Looking For

Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent work experience.
Proven experience in ETL data engineering with significant expertise in using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files.
Proficiency in using Azure Synapse Analytics resources, including Notebooks, Pipelines, Linked Services, and Azure Key Vault.
Demonstrated ability to write complex SQL queries, optimize query performance, and work with data warehousing concepts.
Experience with data quality checks and validation processes.
Strong understanding of data security and compliance with data governance and privacy standards.
Excellent collaboration and communication skills to work effectively with cross-functional teams.

Nice to Have

Certifications related to data engineering or data science, such as Azure Data Engineer.
Experience with Data Fabric concepts, including data lakes and data cataloging.
Familiarity with Agile development methodologies and version control systems like Git.

Benefits and Perks

Opportunity to work on challenging, market-standing projects within a collaborative community.
Continuous learning and professional development opportunities.
Flexible, remote work arrangement with a stipend for home office setup.
Competitive compensation package.
Comprehensive health insurance and wellness programs.
Generous PTO policy and observance of major holidays.
Access to the latest tools and technologies in data engineering and Azure services.

How to Stand Out

Tip: Ensure your portfolio showcases projects that demonstrate your proficiency in Python, Azure Synapse Analytics, and data warehousing, highlighting your ability to work with complex data sets and deliver insights.
When applying, emphasize your experience with ETL processes, data quality checks, and data security measures to stand out as a strong candidate.
Be prepared to discuss your understanding of Data Fabric concepts and how you have applied them in previous roles.
During interviews, ask about the team's dynamics, the company culture, and opportunities for growth and learning to demonstrate your interest in the role and the company.
Consider reaching out to current or former employees to gain insights into the company culture and what it's like to work at Bluelight Consulting, which can aid in your decision-making process and preparation for the role.
Keep your resume and online profiles up-to-date, highlighting relevant certifications, such as Azure Data Engineer, and any courses or training in data engineering and related technologies.

This is a remote position listed on WFA Digital, the platform for professionals who work from anywhere. Browse more remote jobs across all categories.