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Professional Data Jobs (NOW HIRING)

Accenture Federal Services

Data Engineer

$117K - $140K/yr

... Professional Data Engineer, IBM Certified Data Engineer, or similar Company : Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the ...

IT America Inc

GCP Data Engineer

Richardson, TX · On-site

$104K - $124K/yr

GCP Professional Data Engineer or Associate Cloud Engineer certification. * Experience with Apache Beam, Kafka, or similar streaming frameworks. * Familiarity with CI/CD pipelines for data ...

Kaav Inc.

Data Engineer - Azure Data Factory

Addison, TX · Hybrid

$110K - $133K/yr

Required Skills & Qualifications * 3-6 years of professional Data Engineering experience. * Strong hands-on expertise with Azure Data Factory (ADF) and building ETL/ELT pipelines . * Experience with ...

Capital One

Manager, Data Analysis

New York, NY

Lead a team of talented junior analysts on an exciting professional journey while mentoring them ... Mining data to arrive at specific and crucial information for the organization * Identifying and ...

Capital One

Manager, Data Analysis

New York, NY · On-site

Lead a team of talented junior analysts on an exciting professional journey while mentoring them ... Mining data to arrive at specific and crucial information for the organization * Identifying and ...

Accenture Federal Services

Data Engineer

$117K - $140K/yr

... Professional Data Engineer, IBM Certified Data Engineer, or similar Company : Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the ...

Capital One

Manager, Data Analysis

Mclean, VA

Lead a team of talented junior analysts on an exciting professional journey while mentoring them ... Mining data to arrive at specific and crucial information for the organization * Identifying and ...

Accenture Federal Services

Data Engineer

$117K - $140K/yr

... Professional Data Engineer, IBM Certified Data Engineer, or similar Company : Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the ...

Accenture Federal Services

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

... Professional Data Engineer, IBM Certified Data Engineer, or similar Company : Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the ...

Accenture Federal Services

Data Engineer

$117K - $140K/yr

... Professional Data Engineer, IBM Certified Data Engineer, or similar Company : Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the ...

The Data Sherpas

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

Google Professional Data Engineer certification is required. * Strong proficiency with GCP services such as BigQuery, Cloud Dataflow, Cloud Composer, Cloud Pub/Sub, Firestore, and Cloud Functions.

The Data Sherpas

Data Engineer - GCP

Atlanta, GA · On-site

$110K - $132K/yr

Google Professional Data Engineer certification is required. * Strong proficiency with GCP services such as BigQuery, Cloud Dataflow, Cloud Composer, Cloud Pub/Sub, Firestore, and Cloud Functions.

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All JobsProfessional Data Jobs

Professional Data information

What are the highest paying jobs in data?

High-paying data roles include Data Science Managers, Data Architects, and Machine Learning Engineers, often requiring advanced skills in programming, statistics, and cloud platforms. These positions typically offer six-figure salaries and may require certifications like AWS or Google Cloud, along with several years of experience.

Is 40 too late for data science?

Professional data science roles do not have strict age limits, and many individuals start or transition into data science careers at age 40 or later. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, as well as building a strong portfolio and experience. Age should not be a barrier if you are committed to learning and adapting to industry demands.

What are the key skills and qualifications needed to thrive as a Data Professional, and why are they important?

To thrive as a Data Professional, you need strong analytical skills, a solid understanding of statistics, and proficiency in data management, generally supported by a degree in computer science, statistics, or a related field. Familiarity with programming languages like Python or R, experience with SQL databases, and knowledge of data visualization tools such as Tableau or Power BI are typically required. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills in this role. These skills are essential for transforming raw data into actionable insights that drive business decisions and strategies.

What are the most common challenges faced by professionals working in data roles, and how can they be addressed?

Professionals in data roles often encounter challenges such as managing large and complex datasets, ensuring data quality, and keeping up with rapidly evolving tools and technologies. Collaboration with cross-functional teams can also present difficulties, especially when translating technical findings into actionable business insights. Addressing these challenges typically involves ongoing learning, clear communication with stakeholders, and implementing effective data governance practices to maintain accuracy and security. Building strong relationships with colleagues in IT, analytics, and business units is also crucial for success.

What is a Professional Data Analyst?

A Professional Data Analyst is a specialist who collects, processes, and interprets large sets of data to help organizations make informed decisions. They use statistical techniques, data visualization tools, and analytical software to identify trends, solve problems, and provide actionable insights. Data analysts often work closely with business teams to ensure that data-driven strategies align with organizational goals. Their role requires strong analytical skills, attention to detail, and proficiency in programming languages such as SQL, Python, or R.

What is the difference between Professional Data vs Data Analyst?

AspectProfessional DataData Analyst
Required CredentialsBachelor's degree in data science, statistics, or related field; often certifications in data managementBachelor's degree in statistics, mathematics, or related field; certifications like Microsoft Excel or SQL often preferred
Work EnvironmentCorporate offices, data centers, or remote settings; involved in data management and strategyOffice environments; focused on data analysis, reporting, and visualization
Employer & Industry UsageUsed across industries like finance, healthcare, and tech for data governance and strategyCommonly employed in business intelligence, marketing, and finance for data interpretation

Professional Data roles focus on managing, organizing, and ensuring data quality, often requiring broader data management skills. Data Analysts primarily interpret data, create reports, and support decision-making through analysis. While both roles work with data, their core responsibilities and skill sets differ, making each essential in different stages of data utilization.

What does a data professional do?

A data professional analyzes, manages, and interprets data to help organizations make informed decisions. They often work with tools like SQL, Python, or data visualization software and may be involved in data cleaning, modeling, and reporting tasks.

Is AI replacing data analysts?

AI is automating certain tasks within data analysis, such as data cleaning and basic reporting, but it does not fully replace data analysts. Data analysts are needed to interpret complex data, develop insights, and make strategic decisions that require human judgment and domain expertise. Skills in data visualization, statistical analysis, and tools like SQL and Python remain essential for the role.
What cities are hiring for Professional Data jobs? Cities with the most Professional Data job openings:
What are the most commonly searched types of Data jobs? The most popular types of Data jobs are:
What states have the most Professional Data jobs? States with the most job openings for Professional Data jobs include:
Professional Data jobs near you

Data engineering-Big data devloper

Prophecy Technologies

Elk Grove, CA • On-site

$120K - $144K/yr

Full-time

Posted 16 days ago

Job description

Responsibilities:
* Design, develop, and maintain data pipelines using Spark, Python, Scala, and Java.
* Write efficient and optimized SQL queries for data extraction, transformation, and loading (ETL) processes.
* Work with DataFrames to manipulate and analyze large datasets.
* Implement data storage and processing solutions using cloud technologies (preferably AWS or GCP).
* Build and maintain real-time data streaming pipelines using MSK/Kafka.
* Utilize S3 for data storage and retrieval.
* Work with data lake technologies like Iceberg.
* Ensure data quality, integrity, and security.
* Collaborate with data scientists and other engineers to understand data requirements and deliver solutions.
* Participate in code reviews and contribute to improving our development processes.
* Troubleshoot and resolve issues in data pipelines and back-end systems.
Qualifications:
* Bachelor's degree in Computer Science or a related field (or equivalent experience).
* 5+ years of experience in back-end development with a focus on data engineering.
Required Skills:
  • Strong proficiency in Spark, Python, Scala, and Java.

* Expertise in SQL and working with relational databases.
* Experience with DataFrames for data manipulation and analysis.
* Experience with cloud technologies (preferably AWS or GCP).
* Experience with message streaming platforms like MSK/Kafka.
* Experience with S3 or similar object storage.
* Experience with data lake technologies like Iceberg.
* Solid understanding of data warehousing concepts.
* Excellent communication and collaboration skills.
Bonus Points:
* Experience with data modeling and schema design.
* Experience with data governance and data quality management.
* Experience with DevOps practices and CI/CD pipelines.
* Relevant certifications (e.g., AWS Certified Data Engineer, Google Cloud Certified Professional Data Engineer).

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