Data Engineer
Full Time • Aventura, FL
Data Engineer
Overview:
We are seeking an experienced Data Engineer to lead the design, development, and optimization of end-to-end data pipelines and cloud-based solutions. You will be responsible for architecting scalable data and analytic systems, ensuring data integrity, and implementing software engineering best practices and patterns. The ideal candidate has a strong background in ETL, big data technologies, and cloud services, with a proven ability to drive complex projects from concept to production.
Key Responsibilities:
Data Architecture and Engineering
- Design and implement scalable data pipelines for data ingestion, transformation, and storage.
- Architect and optimize data lakes and data warehouses to support analytics and reporting needs.
- Develop robust ETL processes to integrate structured and unstructured data from diverse sources.
- Ensure high data quality through cleaning, validation, and transformation techniques.
Cloud and Big Data Solutions:
- Lead the implementation of big data frameworks such as Hadoop and Spark for processing large datasets.
- Develop and optimize solutions on cloud platforms, including AWS S3, Azure Data Lake, Google BigQuery, and Snowflake.
- Manage data lakes to facilitate efficient data access and processing for downstream applications.
Database and Data Warehousing:
- Design, implement, and manage relational (SQL) and non-relational (NoSQL) database systems.
- Lead database architecture efforts, including schema design, query optimization, and performance tuning.
- Oversee the design and management of data warehouses, ensuring reliability, scalability, and security.
Software Development and Automation:
- Utilize Python and SQL to develop efficient, production-ready code for data pipelines and integrations.
- Implement scripting automation using Bash and PowerShell to streamline workflows.
- Leverage version control (Git) and follow best practices in code optimization, unit testing, and debugging.
Collaboration and Leadership:
- Act as a technical leader, providing guidance on best practices.
- Collaborate with cross-functional teams (Data Scientists, Software Engineers, Analysts) to meet business objectives.
- Drive innovation by evaluating and integrating emerging tools, technologies, and frameworks.
- Establish and maintain CI/CD pipelines to ensure efficient deployment and system reliability.
Required skillset:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
- 5+ years of experience as a Data Engineer with expertise in building large-scale data solutions.
- Proficiency in Python, SQL, and scripting languages (Bash, PowerShell).
- Deep understanding of big data tools (Hadoop, Spark) and ETL processes.
- Hands-on experience with cloud platforms (AWS S3, Azure Data Lake, Google BigQuery, Snowflake).
- Strong knowledge of database systems (SQL, NoSQL), database design, and query optimization.
- Experience designing and managing data warehouses for performance and scalability.
- Proficiency in software engineering practices: version control (Git), CI/CD pipelines, and unit testing.
Preferred:
- Strong experience in software architecture, design patterns, and code optimization.
- Expertise in Python-based pipelines and ETL frameworks.
- Experience with Azure Data Services and Databricks.
- Excellent problem-solving, analytical, and communication skills.
- Experience working in agile environments and collaborating with diverse teams.
Compensation: $125,000.00 - $140,000.00 per year
Our Tech-Nique is the difference.
The technical recruiting industry has rapidly changed over the past decade. What was once a "people" business, driven by relationships, has become transactional and volume based. Candidates have become names in databases, agencies are one of thirty on a vendors list, judged by a KPI. A client is a priority number on a recruiter's hot sheet based on bill rate, fee percentage and ease of fill.
The days of understanding a candidates personal desires and career trajectory or an organization’s cultural nuances and technical environment have shifted to mass resume submissions, distribution lists, and vendor management systems. Generic job descriptions are normal. Everything looks the same. Face to face meetings have been replaced with video & emails and resumes are doctored to match job descriptions.
Recruitment is an art and a science. The recipe for success does not lie in a company's size or its tools, but rather, in the people it employs. It takes talent to find talent. Success in this industry depends on effective communication with all parties, while accurately and transparently setting and managing expectations.