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Data Analyst
$91k-119k (estimate)
Full Time 1 Month Ago
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Singer Industrial is Hiring a Data Analyst Near Dallas, TX

Job Summary:

Singer Industrial is one of America’s largest Industrial Distributors with a North American footprint of approximately 100 locations with over 1,400 employees. Singer Industrial strives to efficiently improve customer productivity with innovative industrial solutions, while providing employee growth and opportunity. We do this with a robust line of fluid power, hose & fittings, belts, seals & gaskets, pneumatic and automation products and services. We are committed to leveraging data to drive informed decision-making and streamline our operations. As we embark on an ERP conversion project, we are seeking a talented and motivated Data Analyst to join our team and play a crucial role in cleansing, structuring, and formatting data to ensure a smooth transition to our new ERP system.

We are looking for a Data Analyst with a strong aptitude for data cleansing, data structuring, and process optimization. The successful candidate will be responsible for preparing data for ERP conversions, ensuring data accuracy, and establishing robust processes to maintain data integrity. This role will be pivotal in helping our organization harness the power of clean, structured data to improve our business operations. This role will be located on site in our office in Dallas, TX.


Duties/Responsibilities:

  • Review and clean large datasets to identify and rectify inconsistencies, inaccuracies, and duplicates.
  • Transform raw data into a standardized format suitable for integration into the ERP system, ensuring compatibility with existing systems.
  • Verify data accuracy, completeness, and consistency to minimize data errors during the ERP conversion process.
  • Collaborate with cross-functional teams to map data from existing systems to the new ERP system, ensuring a seamless transition.
  • Maintain comprehensive documentation of data sources, cleansing procedures, and conversion processes for reference and auditing purposes.
  • Implement best practices to improve data quality and establish data governance policies to maintain data integrity.
  • Develop and implement data cleansing and conversion workflows to streamline and automate data-related tasks.
  • Collaborate with IT and other teams to ensure that data is properly integrated into the new ERP system.
  • Training and Support: Provide training and support to end-users to ensure they can effectively work with the data in the ERP system.
  • Generate reports and provide insights on data quality, progress, and issues to management.


Requires Skills/Abilities:

  • Proficiency in data manipulation tools and languages (e.g., SQL, Python, Excel).
  • Experience with Epicor Prophet 21 (P21) is a plus
  • Understanding of emerging AI technologies around data a plus
  • Familiarity with ERP systems and data migration.
  • Strong problem-solving and analytical skills.
  • Excellent attention to detail and data accuracy.
  • Solid communication and collaboration skills.
  • Ability to work independently and as part of a team.
  • Knowledge of data management and data governance best practices is a plus.


Education and Experience:

  • Bachelor's degree in Data Science, Computer Science, Information Technology, or a related field.
  • Proven experience as a Data Analyst, preferably with a focus on data cleansing and data structuring.
  • Current permanent U.S. work authorization required – no sponsorship.


Physical Requirements:

  • Prolonged periods of sitting at a desk and working on a computer.

Job Summary

JOB TYPE

Full Time

SALARY

$91k-119k (estimate)

POST DATE

03/21/2024

EXPIRATION DATE

05/20/2024

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The following is the career advancement route for Data Analyst positions, which can be used as a reference in future career path planning. As a Data Analyst, it can be promoted into senior positions as a Data Analyst IV that are expected to handle more key tasks, people in this role will get a higher salary paid than an ordinary Data Analyst. You can explore the career advancement for a Data Analyst below and select your interested title to get hiring information.

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If you are interested in becoming a Data Analyst, you need to understand the job requirements and the detailed related responsibilities. Of course, a good educational background and an applicable major will also help in job hunting. Below are some tips on how to become a Data Analyst for your reference.

Step 1: Understand the job description and responsibilities of an Accountant.

Quotes from people on Data Analyst job description and responsibilities

A data analyst also helps the business use the present data to make better business decisions and deliver better services to consumers.

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Their role will be like to work on collaborative, multidisciplinary teams with leaders where they can review and analyze data and to develop the presentation for the data consumption across the organization.

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Data analysts work constantly with stakeholders, fellow colleagues and data suppliers, so good communication skills are essential.

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Many data analysts are required to create presentations of their findings to share with stakeholders and other key members of an organization.

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Gathered requirements, analyze data and create functional/technical specifications to functionality required by new business rules, regulations or standards change.

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Step 2: Knowing the best tips for becoming an Accountant can help you explore the needs of the position and prepare for the job-related knowledge well ahead of time.

Career tips from people on Data Analyst jobs

Data analysts typically work with existing data to solve defined business problems.

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Data analysts rely on various tools to collect and make sense of their data.

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Banks and financial firms need data analysts for financial reporting and forecasting.

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Data analysts often work directly with more senior data team members like data scientists or data engineers.

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Predictive analysis refers to a data analyst's ability to use data, machine learning and statistical algorithms to predict the likelihood of future outcomes based on previous historical data.

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Step 3: View the best colleges and universities for Data Analyst.

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