This is an entry-level engineering position well-suited for early-career professionals seeking ... as Tableau, Power BI, Databricks SQL, or Grafana. • Experience with or strong interest in ...
This is an entry-level engineering position well-suited for early-career professionals seeking ... as Tableau, Power BI, Databricks SQL, or Grafana. • Experience with or strong interest in ...
Entry Level Tableau information
What are the key skills and qualifications needed to thrive in the Entry Level Tableau position, and why are they important?
To thrive as an Entry Level Tableau professional, you need a solid understanding of data analysis, basic database concepts, and visualization techniques, usually supported by a bachelor’s degree in a related field or equivalent experience. Proficiency with Tableau Desktop, Excel, and possibly introductory knowledge of SQL or similar data query tools is often required, and Tableau certification can be an asset. Strong problem-solving skills, detail orientation, and effective communication help individuals excel in gathering requirements and presenting data insights to stakeholders. These skills are essential for transforming raw data into actionable business findings and supporting informed decision-making within an organization.
Is it hard to get a data analyst job with no experience?
Entry level data analyst roles, including those requiring Tableau skills, often accept candidates with limited or no professional experience if they have relevant training, certifications, or strong analytical skills. Building a portfolio of projects and gaining familiarity with tools like Excel, SQL, and Tableau can improve chances of securing such positions. Entry level positions typically focus on potential and willingness to learn, making experience less of a barrier for newcomers with the right skills and motivation.
What types of projects or tasks can I expect to work on as an Entry Level Tableau professional?
As an Entry Level Tableau professional, you will typically work on tasks such as preparing datasets, building interactive dashboards, and assisting more senior analysts with routine reporting. Your day-to-day responsibilities might include gathering requirements from business users, cleaning and importing data, and visualizing trends to address specific business questions. You will often collaborate with other analysts, IT staff, and business stakeholders to ensure reports are accurate and meet organizational needs. Over time, you may also be given opportunities to lead more complex projects as your proficiency with Tableau and your understanding of business processes grow.
Is Tableau worth learning in 2026?
Entry Level Tableau skills remain valuable in 2026 as data visualization and business intelligence are increasingly important across industries. Learning Tableau can enhance job prospects, especially when combined with skills in data analysis, SQL, and certifications like Tableau Desktop Specialist. Its user-friendly interface and widespread adoption make it a useful tool for entry-level data roles.
What is an Entry Level Tableau job?
An Entry Level Tableau job is a position for individuals new to data visualization and analysis using Tableau. Responsibilities typically include creating dashboards, generating reports, and analyzing data to support decision-making. Employers seek candidates with basic Tableau skills, familiarity with databases, and a strong analytical mindset. This role provides a foundation for growth into data analyst or business intelligence positions.
Do I need coding for Tableau?
Entry Level Tableau roles typically do not require extensive coding skills, as Tableau is designed for data visualization through a user-friendly interface. Basic knowledge of data concepts and familiarity with formulas or calculated fields can be helpful, but most tasks can be performed without programming. Advanced roles may involve scripting or integrating with other tools, but for entry-level positions, coding is generally not mandatory.
Are Tableau jobs in demand?
Tableau jobs are in demand as organizations increasingly rely on data visualization and analytics tools to make informed decisions. Entry-level Tableau roles often require knowledge of data analysis, visualization skills, and familiarity with the Tableau platform, making them valuable in data-driven industries.
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Job description
Job Description Everforth ECS is seeking a Junior Data Engineer to work in the National Capital Region covering the Pentagon, Falls Church, and Fairfax . Please Note: This position is contingent upon contract award. The War Data Platform (WDP) is a key initiative within the U.S. Department of War's (DoW) AI-First strategy introduced in early 2026. The WDP separates business and financial data from operational warfighting data, aiming to accelerate the deployment of artificial intelligence (AI) on the battlefield. The WDP extends to Unclassified, Secret, and Top Secret environments, and supports collaboration between Combatant Commands, Joint Staff directorates, Senior Executive Service leaders, and operational analysts. The Junior Data Engineer supports the construction and day-to-day operation of WDP data pipelines across multiple classification enclaves, contributing to the platform's mission of delivering reliable, analytics-ready data to warfighters and mission partners. This is an entry-level engineering position well-suited for early-career professionals seeking hands-on experience in enterprise data engineering within a classified federal environment. • Supports construction and operation of War Data Platform (WDP) Core Integration data pipelines by developing ingestion, transformation, and movement components across Unclassified and NIPR, Secret and SIPR, and Top Secret and JWICS enclaves.
• Configures structured data flows using Apache Airflow, AWS Glue jobs, Spark scripts, and Kafka topics under guidance from senior engineering personnel.
• Performs data preparation tasks including schema mapping, format conversions, metadata tagging, and movement into bronze, silver, and gold medallion tiers.
• Executes baseline quality checks using profiling tools, validation rules, and drift-monitoring alerts to detect abnormalities within lake environments.
• Applies approved security, IAM, and data-handling patterns under guidance from senior engineers and cybersecurity personnel to support cybersecurity requirements for operational data handling.
• Supports Tier-2 and engineering teams by performing basic log review, triage steps, and documented remediation actions for data ingestion or transformation failures.
• Updates technical documentation, workflow diagrams, and pipeline inventories within SharePoint, Confluence, and GitLab repositories.
• Tracks performance indicators including data freshness, pipeline run duration, and feature availability, contributing analytical inputs for engineering decision-making.
• Coordinates with developers, platform engineers, and data operations specialists to support routine updates, backlog work, and deployment activities.
• Contributes to operational readiness by executing repeatable engineering tasks that maintain pipeline continuity, strengthen data usability, and support enterprise analytics across mission communities.
• Performs other duties as assigned. Required Skills • Current Secret security clearance with the ability to obtain and maintain a Top Secret (TS) security clearance with Sensitive Compartmented Information (SCI).
• Up to 3 years of experience in data engineering, software development, or a closely related technical discipline, with foundational exposure to data pipeline construction, ETL workflows, or cloud-based data platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Working knowledge of Python and/or SQL, with familiarity with at least one data orchestration or processing tool such as Apache Airflow, Apache Spark, or AWS Glue. Desired Skills • Active Top Secret (TS) security clearance with Sensitive Compartmented Information (SCI) eligibility.
• Prior internship, academic project, or professional experience supporting data engineering or analytics work in a federal, defense, or intelligence community environment.
• Exposure to medallion architecture data lake design patterns, data quality monitoring techniques, or metadata and lineage management practices.
• Familiarity with DevSecOps practices, Agile or SAFe development methodologies, or version control and collaboration tools such as GitLab, GitHub, or Confluence.
• Experience with data visualization or dashboard reporting tools such as Tableau, Power BI, Databricks SQL, or Grafana.
• Experience with or strong interest in designing semantic data interfaces, metadata layers, or API-based data products that enable automated workflows, AI assistants, and emerging agentic AI capabilities. ECS Federal LLC is an equal opportunity employer and does not discriminate or allow discrimination on the basis any characteristic protected by law. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, or local jurisdiction law. is the federal segment of , a $4B global organization with over 10,000 employees. Our nearly 3,500 professionals deliver advanced technology solutions in data and AI, cybersecurity, and enterprise transformation, serving defense, intelligence, and federal civilian agencies. Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow. We value: * Attracting and developing top talent and high-performing teams * Fostering a culture that is engaging, accountable, and mission-driven
• Configures structured data flows using Apache Airflow, AWS Glue jobs, Spark scripts, and Kafka topics under guidance from senior engineering personnel.
• Performs data preparation tasks including schema mapping, format conversions, metadata tagging, and movement into bronze, silver, and gold medallion tiers.
• Executes baseline quality checks using profiling tools, validation rules, and drift-monitoring alerts to detect abnormalities within lake environments.
• Applies approved security, IAM, and data-handling patterns under guidance from senior engineers and cybersecurity personnel to support cybersecurity requirements for operational data handling.
• Supports Tier-2 and engineering teams by performing basic log review, triage steps, and documented remediation actions for data ingestion or transformation failures.
• Updates technical documentation, workflow diagrams, and pipeline inventories within SharePoint, Confluence, and GitLab repositories.
• Tracks performance indicators including data freshness, pipeline run duration, and feature availability, contributing analytical inputs for engineering decision-making.
• Coordinates with developers, platform engineers, and data operations specialists to support routine updates, backlog work, and deployment activities.
• Contributes to operational readiness by executing repeatable engineering tasks that maintain pipeline continuity, strengthen data usability, and support enterprise analytics across mission communities.
• Performs other duties as assigned. Required Skills • Current Secret security clearance with the ability to obtain and maintain a Top Secret (TS) security clearance with Sensitive Compartmented Information (SCI).
• Up to 3 years of experience in data engineering, software development, or a closely related technical discipline, with foundational exposure to data pipeline construction, ETL workflows, or cloud-based data platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Working knowledge of Python and/or SQL, with familiarity with at least one data orchestration or processing tool such as Apache Airflow, Apache Spark, or AWS Glue. Desired Skills • Active Top Secret (TS) security clearance with Sensitive Compartmented Information (SCI) eligibility.
• Prior internship, academic project, or professional experience supporting data engineering or analytics work in a federal, defense, or intelligence community environment.
• Exposure to medallion architecture data lake design patterns, data quality monitoring techniques, or metadata and lineage management practices.
• Familiarity with DevSecOps practices, Agile or SAFe development methodologies, or version control and collaboration tools such as GitLab, GitHub, or Confluence.
• Experience with data visualization or dashboard reporting tools such as Tableau, Power BI, Databricks SQL, or Grafana.
• Experience with or strong interest in designing semantic data interfaces, metadata layers, or API-based data products that enable automated workflows, AI assistants, and emerging agentic AI capabilities. ECS Federal LLC is an equal opportunity employer and does not discriminate or allow discrimination on the basis any characteristic protected by law. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, or local jurisdiction law. is the federal segment of , a $4B global organization with over 10,000 employees. Our nearly 3,500 professionals deliver advanced technology solutions in data and AI, cybersecurity, and enterprise transformation, serving defense, intelligence, and federal civilian agencies. Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow. We value: * Attracting and developing top talent and high-performing teams * Fostering a culture that is engaging, accountable, and mission-driven