Analytics Engineer

Position Purpose:
The Analytics Engineer is a critical role intended for an innovative, meticulous, and results-oriented professional with a proven background in data analytics and engineering. This position is primarily responsible for optimizing and expanding our data pipeline, developing robust data models to facilitate business interpretation, and driving data-focused decision-making across the organization. Our ideal candidate will seamlessly bridge technical and non-technical stakeholders, implement scalable solutions for large datasets, and excel in supporting the data science team while thriving in our fast-paced corporate setting.

Key Responsibilities:
- Design, build, and manage the Company's data pipeline using appropriate ETL tools to integrate a diverse range of data sources, facilitating data-driven insights for business improvement.
- Collaborate effectively with both technical and non-technical stakeholders to accurately translate business needs into actionable data engineering tasks, ensuring solutions align with company objectives.
- Create and refine data models that effectively simplify and elucidate complex business data, empowering colleagues and teams with clear, meaningful metrics.
- Continually work to enhance data ETL processes for heightened efficiency and quality, ensuring swift, accurate data provision to all relevant departments.
- Develop and maintain scalable data solutions capable of managing large data sets, fortifying the organization's capacity for comprehensive data analysis.
- Provide essential support to the data science department, undertaking data cleaning, data mining, and data visualization tasks, and ensuring a consistent supply of reliable, high-quality data.
- Play an active role in the design and enhancement of the company’s analytics infrastructure, promoting data-driven decision-making across the entire organization, and contributing to a culture of innovation and continuous improvement. 
- Stay abreast of emerging trends and developments in data engineering, applying this knowledge to the continuous improvement of the Company's data infrastructure.

Direct Manager Direct Reports:
The Analytics Engineer - Corporate will report directly to the Manager - Analytics Engineering. This influential position involves consistent interaction and collaboration with key stakeholders across the company's business segments. The Analytics Engineer will also work in close collaboration with a diverse team of data scientists and engineers, both providing leadership and learning from peers. 

Although this position does not have direct reports, it is expected to provide guidance and mentorship to junior team members. Therefore, demonstrating strong leadership attributes is a key component of this role, along with the ability to work effectively as part of a collaborative team. The Analytics Engineer will be responsible for communicating complex data concepts and findings to various stakeholders across the organization in a clear, understandable way, enhancing our collective understanding and use of data in business decision-making.

Just so you know, the company will communicate any changes in this reporting structure promptly, contingent on organizational needs.

Travel Requirements:
The Analytics Engineer - Corporate at the Company is expected to travel approximately 10-15% annually, primarily to national destinations, for department collaboration, training, and strategic meetings.

Physical Requirements:
In accordance with the requirements of the Analytics Engineer - Corporate position, the physical requirements include continuous operation of computer hardware and software. This involves extended periods of sitting, sustained visual concentration, manual dexterity to operate standard office machinery, and occasional lifting of objects weighing up to 20 pounds.  

Miscellaneous physical activities may involve filing, opening cabinets, moving from one location to another within the corporate building for meetings, and occasional travel-related activities, as required by the nature of the job.

The Company abides by the Americans with Disabilities Act (ADA). It will provide reasonable accommodation to applicants with disabilities when necessary, unless such accommodation would pose an undue hardship for the Company. Candidates needing accommodation during the recruitment process are encouraged to contact our HR Department. 

Our commitment to inclusivity ensures we appreciate and respect that individual capabilities are unique. Consequently, if there are variations in the way tasks can be done, we will review those modifications while remaining outcome-focused. All employees or job applicants will receive consideration for employment without discrimination, in accordance with the ADA.

Working Conditions:
The Corporate Analytics Engineer will primarily operate from our corporate headquarters, integrating into a highly collaborative and dynamic team environment that thrives on creativity and innovation. The office is a synergistic space that encourages direct communication and engagement with team members, while advanced technology infrastructure enables the retail convenience of working remotely when required. In alignment with our business operations, this is a full-time position with standard business hours, although occasional overtime may be required to meet specific project deadlines. This role involves working in a fast-paced, deadline-driven setting and requires a high degree of resourcefulness, flexibility, and adaptability. As a Fortune 50 company, the Company maintains a culture that promotes problem-solving, clear communication, and initiative as core parts of everyday work. Therefore, this position is best suited to an individual who thrives under pressure, welcomes challenges, and pursues excellence.

Minimum Qualifications:
1. A Bachelor’s degree in Computer Science, Information Systems, or other related field. Advanced degrees or certifications are highly favored.
2. Minimum of 5 years of experience in Analytics engineering roles, ideally in the corporate sector.
3. Dynamic understanding of data analytics and knowledge of various SQL, Python, R, and other programming languages.
4. Comprehensive proficiency in using ETL tools for data processing.
5. Experience working with big data platforms such as Hadoop or Spark.
6. Demonstrable problem-solving capability and a strong analytical thinking capacity.
7. Excellent communication skills, with the ability to clearly articulate complex data understandings to both technical and non-technical personnel.
8. Proficient in functioning in high-pressure, strict deadline environments.
9. Experience in supporting data science teams with tasks such as data cleaning, data mining, and data visualization.
10. Proven track record in working with cross-functional teams and translating business requirements into data engineering initiatives.
11. Demonstrated ability to optimize data extraction, transformation, and loading processes strategically.

Preferred Qualifications:
1. An advanced degree, such as a Master’s or PhD, in a field related to data sciences, computer engineering, or business intelligence.
2. Over seven years of experience in building and maintaining data pipelines, manipulating data sets, and managing large-scale data infrastructure in a corporate setting.
3. Advanced skills in SQL, Python, R, Java, and other programming languages relevant to data engineering.
4. Extensive experience with big data processing tools like Hadoop, Hive, and Spark, as well as data warehousing solutions like Redshift, Snowflake, or BigQuery.
5. Proficiency with data visualization tools such as Tableau, Power BI, D3.js, or QlikView, as well as BI tools such as Looker or SAS.
6. Knowledge of machine learning algorithms, predictive modeling, and statistical analysis techniques would be a definitive advantage.
7. Capacity to effectively pitch and present data-driven insights to senior stakeholders and drive the adoption of a data-first mindset within the organization.
8. Demonstrated ability to manage projects in a fast-paced environment, meet tight deadlines, and consistently deliver high-quality work.
9. Experience working with cross-functional teams, including Business Analytics, IT, and Finance, demonstrating a strong understanding of business strategy and operations.
10. Relevant professional certifications, such as Certified Analytics Professional (CAP) or Certified Data Management Professional (CDMP), would be highly desirable.
11. Track record of driving continuous improvement and innovation in a data management role. 

The preferred qualifications for this role highlight the candidate's potential to not only contribute to the technical aspects of our operations but also drive meaningful change across the organization through data-driven decision-making. This is in line with the Company's commitment to fostering a culture of innovation, excellence, and continuous improvement.

Minimum Education:
Minimum Educational Requirement: The ideal candidate for the Analytics Engineer - Corporate role should hold at least a bachelor's degree in computer science, information systems, or a related field. A master’s degree or its equivalent is highly preferred.

Preferred Education:
A master's degree or Ph.D. in computer science, data science, information systems, or a related field from an accredited institution would be highly valued. Additional certifications in data analytics or related courses are also appreciated.

Minimum Years Of Work Experience:
The ideal candidate for the Analytics Engineer - Corporate position with the Company must have at least 5 years of highly relevant experience in data analytics and data engineering. It is preferred that this experience be within a corporate environment.

Certifications:
1. Certified Analytics Professional (CAP) – This globally recognized professional certification would serve as proof of your end-to-end understanding of the analytics process.

2. Microsoft Certified: Azure Data Engineer Associate – This certification is preferred as it demonstrates your ability to implement and manage data solutions using Microsoft's Azure platform.

3. Google Certified Professional - Data Engineer – Candidates possessing this certification will be able to showcase their expertise in designing, building, maintaining, and troubleshooting data processing systems with Google Cloud technologies.

4. Certified Data Management Professionals (CDMP) – A high-value certification demonstrating dedication to best practices in data management.

5. SAS Certified Big Data Professional – A preferred certification that demonstrates your skills in manipulating and gaining insights from big data with a variety of SAS and open source tools.

6. AWS Certified Big Data - Specialty – This establishes your ability to automate data analysis processes, secure data, and leverage AWS services to design and implement big data environments.

7. IBM Certified Data Engineer – Big Data - This sought-after certification verifies your foundational knowledge of data engineering principles, along with your expertise in applying it for practice.

8. Cloudera Certified Data Engineer – Certification that displays proficiency in data ingestion, transformation, storage, and analysis processes in Cloudera’s CDH environment.

9. Tableau Certified Data Analyst – Preferred for its illustration of your ability to navigate, manage, and create impactful visualizations on the Tableau platform.

For all certifications, a valid and current status is required. Candidates should be prepared to provide proof of certifications during the recruitment process. This list is not exhaustive, and other relevant industry certifications will also be considered.

Competencies:
1. Data Analytics Proficiency: Ability to design, develop, and maintain data models and manage the data pipeline—experience in optimizing data extraction, transformation, and loading processes. 
   
2. Technical Aptitude: Profound knowledge of SQL, Python, R, and other programming languages and ETL tools. Familiarity with big data platforms like Hadoop, Spark, and others.

3. Business Problem-Solving Ability: Ability to solve complex business problems using data insights. Experience in developing scalable solutions to handle large data sets. 

4. Stakeholder Management Skills: Expertise in working with both technical and non-technical stakeholders, translating business requirements into data engineering tasks.

5. Communication Skills: Ability to clearly articulate complex data insights, fostering better understanding among team members and stakeholders. 
  
6. Project Management Skills: Ability to thrive in a fast-paced, results-driven environment under tight deadlines. Can manage and lead projects effectively from conception to completion.

7. Advanced Education: Preferably a master’s degree or equivalent in computer science, information systems, or a related field.

8. Industry Experience: A minimum of five years of relevant experience in data analytics, data engineering, or related functions in a corporate setting.
 

      

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As an Equal Employment Opportunity (EEO) employer SRS Distribution Inc., including all its subsidiaries, provides job opportunities to qualified individuals without regard to actual or perceived race, color, creed, religion, national origin, sex, gender, age, disability, gender identity, sexual orientation, citizenship status, uniform service, veteran status, marital status, genetic information, physical or mental disability, or any other characteristic in accordance with applicable federal, state, and local EEO laws. If you are an individual with a disability or a disabled veteran and require a reasonable accommodation in applying for any posted position, please contact Human Resources at US: 855.556.3221, or by email to: [email protected] with the nature of your accommodation request and include the Business name, location and title of the job opening. Please allow one (1) business day for a reply. All employment offers are contingent upon successful completion of a background check and drug screen, as permitted by law.

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Competitive weekly/bi-weekly pay, discretionary bonuses, 401(k) with company match, Employee Stock Purchase Plan, paid time off (vacation, sick, volunteer, holidays, birthday, floating), medical/dental/vision, flexible spending accounts, company-paid life and short-term disability, plus optional long-term disability, and additional life insurance.

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