Senior Data Engineer - Orlando, Florida, United States

Only for registered members Orlando, Florida, United States

11 hours ago

$64,750 - $69,750 (USD) per year

Senior Data Engineer - 6 month contract to hire role · Location: Hybrid Model in Orlando, FL: · In-Office: Monday, Tuesday, Wednesday · Work-From-Home (WFH): Thursday, Friday · Pay: $50-$52.75/hr · ***Candidates must be a green card holder or U.S. Citizen. No sponsorship will be ...

Job description

Senior Data Engineer - 6 month contract to hire role

Location: Hybrid Model in Orlando, FL:

In-Office: Monday, Tuesday, Wednesday
Work-From-Home (WFH): Thursday, Friday

Pay: $50-$52.75/hr

***Candidates must be a green card holder or U.S. Citizen. No sponsorship will be provided for this role.

Schedule: Mon - Fri 8:00a-5:00p

Position Summary

The Senior Data Engineer will be a key partner to various business teams, responsible for designing, implementing, and maintaining robust analytical and data solutions that drive business value and enhance customer satisfaction. This role requires an experienced professional focused on the entire data lifecycle: collecting, storing, processing, analyzing, and modeling large, complex datasets. The primary focus will be on building, maintaining, implementing, monitoring, supporting, and integrating scalable data pipelines and applications within the company's enterprise architecture.

How You'll Shine (Key Responsibilities)

Data Pipeline Development: Design, implement, test, deploy, and maintain stable, secure, and scalable data engineering solutions and pipelines (ETL/ELT). This includes integrating new sources of data into the central data warehouse and ensuring data movement to downstream applications and affiliates.
Infrastructure Management: Maintain and monitor our analytics data warehouses, including Snowflake, and the overall data platform health.
Hands-On Solutions: Be responsible for hands-on development, deployment, maintenance, and support of a variety of Cloud and on-premise solutions, web service infrastructure, and supporting technologies.
Automation & Optimization: Produce scalable, replicable code and engineering solutions that help automate repetitive data management tasks and optimize data flow performance.
Cross-Functional Partnership: Work closely with Project Managers, Business Analysts, Data Scientists, and other organizational groups to translate functional requirements and business processes into detailed technical specifications.
Strategic Alignment: Collaborate with key stakeholders to ensure our data infrastructure meets business needs in a secure and scalable way. Keep a critical eye on the technical strategy, identify gaps, and propose creative, forward-thinking solutions.

Essential Qualifications / Education & Experience

Experience: 3+ years of related professional experience in Data Engineering or IT.
Equivalency: Experience equivalent to the education requirement may be accepted.
Required Education: Bachelor's degree in Computer and Information Science.
Preferred Education: Master's degree.

Technical Expertise

Cloud/Big Data Ecosystems (1+ years): Proven experience working with Apache Spark framework, Hadoop, Java/Scala, Python, and AWS architecture.
Database & Modeling (2+ years): Experience in data modeling/database development using PL/SQL and SQL Server 2016 or later and Snowflake.
Data Pipelines & ETL (1+ years): Proven experience building data pipelines and ETL/ELT flows in Cloud and on-premise environments using tools like Snowpipe, Informatica, Airflow, and/or Kafka.
Application Development (1+ years): Proven experience in Microsoft .Net technologies such as C# and VB.Net, including designing, developing, and deploying Windows & Web applications.

Core Skills & Abilities

Database Proficiency: Strong working SQL knowledge and experience with relational databases, query authoring, and familiarity with a variety of database platforms.
Data Pipeline Optimization: Proven experience building and optimizing data pipelines and data sets leveraging various scripting languages or ETL tools.
Data Manipulation: A successful history of manipulating, processing, and extracting value from large, disconnected, and unstructured datasets.
Problem Solving: Ability to perform root cause analysis on internal and external data processes to answer specific business questions and identify opportunities for improvement.
APIs: Ability to build and use APIs to push and pull data from various data systems and platforms.
Systemic Thinking: Excellent ability to analyze information and think systematically.
Certification (Preferred): Snowflake and Python certification are a strong plus.

Professional Attributes

Communication: Excellent listening, interpersonal, communication (written & verbal), and problem-solving skills.
Detail-Oriented: Extremely organized with great attention to detail.
Business Acumen: Good understanding of the company's business processes and the industry at large.
Teamwork: A strong team player with the ability to work independently when necessary.

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