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Professional Data Jobs in Washington (NOW HIRING)

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Professional Data information

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 are the key skills and qualifications needed to thrive as a data professional?

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 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 professional data do?

A professional data role involves collecting, analyzing, and interpreting data to support decision-making within an organization. They often use tools like SQL, Excel, or data visualization software and require strong analytical skills and attention to detail. Their work helps improve business processes, identify trends, and inform strategic planning.

What are the most commonly searched types of Data jobs in Washington?

The most popular types of Data jobs in Washington are:

What cities in Washington are hiring for Professional Data jobs?

Cities in Washington with the most Professional Data job openings:

$129K - $155K/yr

Full-time

Re-posted 28 days ago


Accenture Federal Services rating

8.7

Company rating: 8.7 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

51st of 500 rated business services


Job description

The work: 

  • Pipeline Architect: Design, build, and maintain scalable end-to-end data pipelines using Databricks, Spark, and related technologies. 
  • Transformation Titan: Develop efficient data processing and transformation workflows to support analytics and reporting needs. 
  • Integration Hero: Integrate diverse data sources including APIs, databases, and cloud storage into unified datasets. 
  • Collaboration Champion: Work closely with cross-functional teams (data science, analytics, business units) to design and implement data solutions that align with business goals. 
  • Quality Guardian: Implement robust validation, monitoring, and observability processes to ensure data accuracy, completeness, and reliability. 
  • Automation Avenger: Contribute to data governance, security, and automation initiatives within the data ecosystem. 
  • Cloud Commander: Leverage AWS services (e.g., S3, Glue, Lambda, Redshift) to build and deploy data solutions in a cloud-native environment. 

Here's what you need: 

  • Experience with cloud-based ETL services (e.g. AWS Glue, Google Cloud Dataflow, Azure Data Factory) 
  • Experience with Cloud data warehousing technologies (e.g. Amazon Redshift, Google BigQuery, Snowflake) 
  • Experience with Python, SQL, Spark, and PySpark 
  • Experience with data platforms like Databricks, Palantir, and Snowflake 
  • Familiarity with data orchestration and data quality processes 
  • Must be a US Citizen

Bonus points if you have: 

  • Secret clearance or above 
  • Experience working with federal clients 
  • Experience with COTS and open-source data engineering tools such as ElasticSearch and NiFi 

  • Experience with Docker/Kubernetes Hadoop/Spark, NiFi, ELK stack 
  • Experience with Agile / Scrum

  • Data engineering certification such as Palantir Foundry Data Engineer, Azure Data Engineer Associate, Google Professional Data Engineer, IBM Certified Data Engineer, or similar 

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