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Data Engineer

ReturnPro
Posted 6 months ago, valid for 17 days
Location

Miami, FL 33111, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • The job is for a Data Engineer position located in Miami, FL, requiring full-time commitment with standard working hours from 9 am to 6 pm.
  • Candidates must have a Bachelor鈥檚 or Master鈥檚 degree in Computer Science, Data Engineering, or a related field, along with at least 5 years of experience in building large-scale data solutions.
  • The role involves designing and optimizing data pipelines, implementing big data frameworks, and managing cloud-based solutions across platforms like AWS and Azure.
  • Proficiency in Python, SQL, and scripting languages, as well as a deep understanding of ETL processes and database systems, is essential for the position.
  • The salary for this role is not explicitly stated in the job description, but it typically aligns with industry standards for experienced Data Engineers in similar locations.

Job DetailsJob Location: FL Miami - Aventura, FL 33180Position Type: Full TimeJob Shift: HQ: Standard 9am to 6pmWe 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. 聽 Primary Responsibilities/Essential Functions 聽 This job description in no way states or implies that these are the only duties to be performed by the teammate occupying this position. The selected candidate may perform other related duties assigned to meet the ongoing needs of the business. 聽 Key Responsibilities 聽 Data Architecture and Engineering 路 Design and implement scalable data pipelines for data ingestion, transformation, and storage. 路 Architect and optimize data lakes and data warehouses to support analytics and reporting needs. 路 Develop robust ETL processes to integrate structured and unstructured data from diverse sources. 路 Ensure high data quality through cleaning, validation, and transformation techniques. 聽 Cloud and Big Data Solutions 路 Lead the implementation of big data frameworks such as Hadoop and Spark for processing large datasets. 路 Develop and optimize solutions on cloud platforms, including AWS S3, Azure Data Lake, Google BigQuery, and Snowflake. 路 Manage data lakes to facilitate efficient data access and processing for downstream applications. 聽 Database and Data Warehousing 路 Design, implement, and manage relational (SQL) and non-relational (NoSQL) database systems. 路 Lead database architecture efforts, including schema design, query optimization, and performance tuning. 路 Oversee the design and management of data warehouses, ensuring reliability, scalability, and security. 聽 Software Development and Automation 路 Utilize Python and SQL to develop efficient, production-ready code for data pipelines and integrations. 路 Implement scripting automation using Bash and PowerShell to streamline workflows. 路 Leverage version control (Git) and follow best practices in code optimization, unit testing, and debugging. 聽 Collaboration and Leadership 路 Act as a technical leader, providing guidance on best practices. 路 Collaborate with cross-functional teams (Data Scientists, Software Engineers, Analysts) to meet business objectives. 路 Drive innovation by evaluating and integrating emerging tools, technologies, and frameworks. 路 Establish and maintain CI/CD pipelines to ensure efficient deployment and system reliability. QualificationsRequired: 路 Bachelor鈥檚 or Master鈥檚 degree in Computer Science, Data Engineering, or a related field. 路 5+ years of experience as a Data Engineer with expertise in building large-scale data solutions. 路 Proficiency in Python, SQL, and scripting languages (Bash, PowerShell). 路 Deep understanding of big data tools (Hadoop, Spark) and ETL processes. 路 Hands-on experience with cloud platforms (AWS S3, Azure Data Lake, Google BigQuery, Snowflake). 路 Strong knowledge of database systems (SQL, NoSQL), database design, and query optimization. 路 Experience designing and managing data warehouses for performance and scalability. 路 Proficiency in software engineering practices: version control (Git), CI/CD pipelines, and unit testing. 聽 Preferred 路 Strong experience in software architecture, design patterns, and code optimization. 路 Expertise in Python-based pipelines and ETL frameworks. 路 Experience with Azure Data Services and Databricks. 路 Excellent problem-solving, analytical, and communication skills. 路 Experience working in agile environments and collaborating with diverse teams.




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