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Data Engineer ID43228 Job Opening In West Palm Beach – Now Hiring AgileEngine


Job description

Job Description
AgileEngine is an Inc.

5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries.

We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.



WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

As a Middle Data Engineer, you’ll build and optimize ETL pipelines and cloud data solutions that provide reliable insights for data scientists and analysts.

You’ll tackle complex data challenges, collaborate with cross-functional teams, and grow your expertise in Python, Airflow, Spark, and AWS in a dynamic, innovative environment.

WHAT YOU WILL DO

- Build and support ETL pipelines;
- Monitor data pipelines, identify bottlenecks, optimize data processing and storage for performance and cost-effectiveness;
- Collaborate effectively with cross-functional teams including data scientists, analysts, software engineers, and business stakeholders;
- Working with Terraform to build AWS infrastructure;
- Analyze sources and build Cloud Data Warehouse and Data Lake solution.

MUST HAVES

- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 3+ years of professional experience with Python;
- 3+ years of professional experience in a Data Engineering role;
- Proficiency in programming languages commonly used in data engineering such as Python, SQL, and optionally Scala for working with data processing frameworks like Spark and libs like Pandas;
- Proficiency in designing, deploying, and managing data pipelines using Apache Airflow for workflow orchestration and scheduling;
- Ability to design, develop, and optimize ETL processes to move and transform data from various sources into the data warehouse, ensuring data quality, reliability, and efficiency;
- Knowledge of big data technologies and frameworks such as Apache Spark for processing large volumes of data efficiently;
- Extensive hands-on experience with various AWS services relevant to data engineering, including but not limited to Amazon MWAA, Amazon S3, Amazon RDS, Amazon EMR, AWS Lambda, AWS Glue, Amazon Redshift, AWS Data Pipeline, Amazon DynamoDB;
- Deep understanding and practical experience in building and optimizing cloud data warehousing solutions;
- Ability to monitor data pipelines, identify bottlenecks, and optimize data processing and storage for performance and cost-effectiveness;
- Excellent communication skills to collaborate effectively with cross-functional teams including data scientists, analysts, software engineers, and business stakeholders;
- Bachelor’s degree in computer science/engineering or other technical field, or equivalent experience;
- Upper-intermediate English level.

NICE TO HAVES

- Familiarity with the fintech industry, understanding of financial data, regulatory requirements, and business processes specific to the domain;
- Documentation skills to document data pipelines, architecture designs, and best practices for knowledge sharing and future reference;
- GCP services relevant to data engineering;
Snowflake;
- OpenSearch, Elasticsearch;
- Jupyter for analyze data;
- Bitbucket, Bamboo;
- Terraform.

PERKS AND BENEFITS

- Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.

- Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.

- A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.

- Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.



Requirements
3+ years of professional experience with Python; 3+ years of professional experience in a Data Engineering role; Proficiency in programming languages commonly used in data engineering such as Python, SQL, and optionally Scala for working with data processing frameworks like Spark and libs like Pandas; Proficiency in designing, deploying, and managing data pipelines using Apache Airflow for workflow orchestration and scheduling; Ability to design, develop, and optimize ETL processes to move and transform data from various sources into the data warehouse, ensuring data quality, reliability, and efficiency; Knowledge of big data technologies and frameworks such as Apache Spark for processing large volumes of data efficiently; Extensive hands-on experience with various AWS services relevant to data engineering, including but not limited to Amazon MWAA, Amazon S3, Amazon RDS, Amazon EMR, AWS Lambda, AWS Glue, Amazon Redshift, AWS Data Pipeline, Amazon DynamoDB; Deep understanding and practical experience in building and optimizing cloud data warehousing solutions; Ability to monitor data pipelines, identify bottlenecks, and optimize data processing and storage for performance and cost-effectiveness; Excellent communication skills to collaborate effectively with cross-functional teams including data scientists, analysts, software engineers, and business stakeholders; Bachelor’s degree in computer science/engineering or other technical field, or equivalent experience; Upper-intermediate English level.

Required Skill Profession

Computer Occupations


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Unlock Your Data Engineer Potential: Insight & Career Growth Guide


Real-time Data Engineer Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Data Engineer in West Palm Beach, United States, highlighting market share and opportunities for professionals in Data Engineer roles.

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at AgileEngine adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying United States laws and regulations

What Is the Average Salary Range for Data Engineer ID43228 Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in West Palm Beach. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for Data Engineer ID43228?

Key qualifications for Data Engineer ID43228 typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Data Engineer ID43228 Job Success

AgileEngine interview tips for Data Engineer ID43228

Here are some tips to help you prepare for and ace your Data Engineer ID43228 job interview:

Before the Interview:

Research: Learn about the AgileEngine's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

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Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

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Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Data Engineer ID43228 interview at AgileEngine, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the AgileEngine's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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