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Data Engineer

Job in Miami, Miami-Dade County, Florida, 33222, USA
Listing for: Gravity IT Resources
Full Time position
Listed on 2026-06-30
Job specializations:
  • Engineering
    Data Engineering
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 100000 - 130000 USD Yearly USD 100000.00 130000.00 YEAR
Job Description & How to Apply Below

Job Title:

Sr Data Engineer

Type: Contract
Location: Miami FL | Dallas, Texas

Company Overview

The Senior Data Engineer will play a pivotal role in building and maintaining scalable, reliable, and high-performance data pipelines and enterprise analytics infrastructure. This role is ideal for someone who thrives in a collaborative environment, enjoys mentoring others, and wants to drive innovation in data engineering across the organization.

Your Responsibilities on the Team
  • Lead the design and implementation of scalable, high-performance data architectures that support diverse data sources, including structured, semi-structured, and unstructured data.
  • Architect and build data pipelines that can process and analyze large-scale datasets in real-time and batch modes.
  • Mentor and guide junior data engineers in best practices, code quality, and technical skills, fostering a culture of continuous learning.
  • Ensure the reliability, efficiency, and security of data pipelines by implementing monitoring, alerting, and automated recovery mechanisms.
  • Collaborate with cross-functional teams, including data scientists, analysts, and product managers, to align data solutions with business needs and goals.
  • Lead the adoption of new technologies and tools that enhance the data engineering capabilities of the team.
  • Oversee the development of data models, schemas, and data marts that enable efficient data analysis and reporting.
  • Implement data governance frameworks, including data lineage, metadata management, and data quality standards.
Your Toolbox
  • Bachelor’s degree in Computer Science, Information Technology, Management Information Systems, or a related field.
  • 6+ years of experience in data engineering or a related role, with demonstrated success in delivering enterprise‑scale data solutions.
  • Proficient in SQL, with the ability to write complex queries, perform query optimization, and conduct performance tuning.
  • Experience with cloud data warehouses like Snowflake, Databricks, and understanding of their appropriate use cases.
  • Strong programming skills in Python or Java, with experience in data processing frameworks (e.g., Apache Spark, Hadoop).
  • Experience with cloud platforms (AWS, Azure, GCP) and administration, such as AWS Redshift, Azure Synapse, or Google Big Query.
  • Proficiency with big data technologies, including Hadoop, Spark, Kafka, and HBase, with experience in distributed data processing.
  • Expertise with data orchestration tools, such as MWAA/Airflow, for scheduling and managing data workflows.
  • Experience with reporting tools such as Power BI and Tableau is a plus.
  • Understanding of data security practices, including encryption, access controls, and data masking.
  • Familiarity with cloud administration tools and frameworks such as AWS, dbt, Qlik Replicate, Tableau, and Snowflake is preferred.
Job Title:

Data Engineer

Type: Contract
Location: Miami FL | Dallas, Texas

Company Overview

The Data Engineer will provide technical leadership to the data platform engineering team by designing and implementing next‑generation data and analytics platforms and products using data engineering best practices. This role is hands‑on, contributing to engineering solutions while enabling business users through self‑service and automation. The Data Engineer is a key role in operationalizing the enterprise data fabric.

Your Responsibilities on the Team
  • Design, Build, and Operationalize: Formulate production‑grade data engineering solutions for enterprise data and analytics platforms and products.
  • Pipeline Architecture: Architect and implement reliable ETL, ELT, and streaming data ingestion and delivery processes across multiple enterprise sources.
  • Modern Python Development: Develop, maintain, and containerize modular data applications and utility scripts using Python on modern cloud infrastructure.
  • Scale and Improve Infrastructure: Enhance data ingestion architecture with emphasis on data quality, cost‑performance, maintainability, and extensibility across storage and compute layers.
  • Enforce Standards and Downstream Integrity: Define and implement engineering standards (code modularization, version control, automated testing, secure CI/CD workflows). Ensure…
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