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About careerzynith
careerzynith is a world‑leading retailer that has transformed the way millions of people shop, save, and live better every day. With a presence in dozens of countries and a digital ecosystem that processes billions of transactions annually, careerzynith relies on data‑driven insights to stay ahead of the competition. Our mission is simple: empower customers to make smarter choices through innovative technology, seamless experiences, and a relentless focus on value. As part of this mission, the Data & Information Modeling team builds the pipelines, data lakes, and analytical frameworks that turn raw information into actionable intelligence.
Why Join careerzynith?
Working at careerzynith means becoming part of a forward‑thinking, technology‑centric culture where every line of code, every data point, and every insight can impact the lives of millions. As a remote employee, you’ll enjoy the flexibility of working from anywhere while collaborating with a global network of engineers, analysts, and business partners. You’ll be at the forefront of retail innovation, helping shape the next generation of data‑driven strategies that drive efficiency, cost savings, and superior customer experiences.
Key Responsibilities
- Partner with the Application Development team to design, implement, and maintain data pipelines that feed critical business applications.
- Develop logical and physical data models using industry‑best practices to ensure high data quality, consistency, and reusability across multiple use cases.
- Create, enhance, and maintain canonical data models that support both new initiatives and existing projects in alignment with business standards.
- Design data modeling solutions optimized for relational, hierarchical, and NoSQL data stores, including Big Data platforms.
- Maintain and document logical, physical, and canonical data models alongside associated metadata repositories.
- Establish and enforce naming conventions and coding standards to promote uniformity across all data models.
- Identify opportunities for model reuse in new scenarios, reducing duplication and accelerating delivery timelines.
- Perform reverse‑engineering of physical data models from existing databases and SQL scripts to understand legacy structures.
- Validate data models and physical data sets for accuracy, completeness, and compliance with business rules.
- Approve business data objects for correctness and completeness, ensuring they meet stakeholder expectations.
- Analyze data integration challenges and propose robust, scalable solutions that align with architectural guidelines.
- Guide Data Engineers, Architects, and Software Developers on project scope, performance requirements, and integration points.
- Recommend enhancements to existing applications to improve performance, scalability, and data integrity.
- Review new application designs and suggest data‑modeling improvements where necessary.
Essential Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field (B.E/B.Tech/M.E/M.Tech/MBA).
- 10+ years of hands‑on experience in data warehousing and data modeling.
- Deep understanding of data modeling techniques for data warehousing – 3NF, dimensional, hierarchical, and hybrid approaches.
- Experience managing large‑scale data environments (100 TB+), including Data Warehouses (DW) and Operational Data Stores (ODS).
- Proven track record building data models for MPP, social, and NoSQL technologies such as Hadoop, Hive, Cassandra, Snowflake, and cloud‑based databases.
- Strong collaboration skills with the ability to work effectively across distributed, cross‑functional teams.
- Excellent communication and influencing abilities, capable of negotiating technical solutions with business stakeholders.
Preferred Qualifications
- Advanced degree (Ph.D. or Master’s) in Computer Science, Data Engineering, or a related discipline.
- Experience in retail, e‑commerce, supply chain, or financial services domains.
- Hands‑on experience with data integration tools (e.g., Informatica, Talend) and ETL processes.
- Familiarity with cloud platforms (AWS, Azure, GCP) and modern data lake architectures.
- Certifications in data modeling, data warehousing, or cloud data services.
- Demonstrated ability to mentor junior team members and lead technical workshops.
Core Skills & Competencies
- Technical Expertise: Proficiency in SQL, PL/SQL, Python, and scripting languages for data manipulation.
- Modeling Tools: Experience with ER/Studio, PowerDesigner, or similar data modeling software.
- Big Data Platforms: Hands‑on knowledge of Hadoop ecosystem components, Spark, and distributed file systems.
- Cloud Services: Familiarity with Amazon Redshift, Azure Synapse, Google BigQuery, and Snowflake.
- Analytical Thinking: Ability to translate complex business requirements into scalable data architectures.
- Collaboration: Strong interpersonal skills to work with data scientists, analysts, product owners, and IT operations.
- Problem‑Solving: Proven track record of diagnosing data quality issues and implementing corrective actions.
- Documentation: Ability to produce clear, concise documentation for data models, metadata, and governance processes.
Career Growth & Learning Opportunities
careerzynith invests heavily in the professional development of its employees. As a Data Modeling Specialist, you will have access to:
- Mentorship programs with senior architects and industry experts.
- Continuous learning subscriptions (Coursera, Pluralsight, O’Reilly) for emerging technologies.
- Opportunities to lead high‑visibility projects that influence global retail strategies.
- Cross‑functional rotations that broaden your expertise in analytics, AI, and cloud engineering.
- Leadership pathways that can transition you into Data Architecture, Enterprise Analytics, or Product Management roles.
Work Environment & Culture
careerzynith embraces a hybrid work model that blends remote flexibility with occasional on‑site collaboration at our innovation hubs. Our culture is built on:
- Inclusivity: A commitment to diversity, equity, and inclusion where every voice is heard.
- Innovation: Encouraging experimentation, rapid prototyping, and data‑driven decision making.
- Collaboration: Virtual “digital cafés” and regular team‑wide syncs to keep remote employees connected.
- Well‑Being: Programs that support mental health, work‑life balance, and personal growth.
- Recognition: Performance‑based awards, peer‑to‑peer shout‑outs, and a transparent feedback culture.
Compensation, Benefits & Perks
careerzynith offers a competitive total rewards package that includes:
- Base salary aligned with market benchmarks for senior data professionals.
- Annual performance bonuses tied to individual and company outcomes.
- Equity participation through stock purchase plans.
- Comprehensive health, dental, and vision coverage for you and your dependents.
- 401(k) retirement plan with generous employer match.
- Paid parental leave, generous PTO, and flexible holidays.
- Wellness stipend, virtual fitness classes, and mental‑health resources.
- Home office allowance to set up an ergonomic remote workspace.
- Continuous learning budget and tuition reimbursement for advanced degrees.
How to Apply
Ready to bring your data expertise to careerzynith? Follow these steps to submit your application:
- Review the official job posting on the careerzynith Careers portal.
- Prepare the required documents: a copy of your degree certificates with transcripts, a recent passport‑size photo, and a digital signature.
- Complete the online application form, attaching the documents listed above.
- Submit your application and await a confirmation email with next steps.
Join Us
If you are passionate about turning massive data sets into strategic assets, thrive in a collaborative remote environment, and want to make a tangible impact on a global retail leader, careerzynith wants to hear from you. Bring your energy, expertise, and enthusiasm to a team that values innovation, diversity, and continuous growth. Apply today and help shape the future of retail data at careerzynith.
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