Senior Data Engineer – Remote Data Integration, Analytics & Insight Generation for Retail Innovation at careerzynith
About careerzynith – Pioneering the Future of Retail Technology
careerzynith is a global leader in retail technology, delivering cutting‑edge data solutions that empower millions of shoppers worldwide. Our mission is to transform the retail experience through intelligent data pipelines, advanced analytics, and innovative platforms that connect merchants, customers, and partners in seamless harmony. As a technology‑driven organization, careerzynith invests heavily in talent, fostering a culture of curiosity, collaboration, and continuous learning. Join us and become part of a team that shapes the future of retail, one data stream at a time.
Position Overview
We are seeking a highly motivated Senior Data Engineer to join our Data Ventures team. This remote role focuses on designing, building, and maintaining robust data pipelines that power critical business insights across careerzynith’s retail ecosystem. You will work closely with data scientists, analysts, product managers, and engineering partners to turn raw, high‑volume data into reliable, actionable information that drives strategic decisions and enhances the customer experience.
Key Responsibilities
- Data Ingestion & Transformation: Architect and implement scalable ETL/ELT pipelines using Hadoop, Spark, Python/PySpark, and Java to ingest data from diverse sources (e.g., transactional systems, clickstreams, IoT devices).
- Data Modeling & Warehouse Design: Design logical and physical data models, including star and snowflake schemas, to support analytical workloads in GCP BigQuery, Snowflake, and other cloud data warehouses.
- Data Quality & Governance: Establish data validation frameworks, automated quality checks, and lineage tracking to ensure data integrity, compliance, and traceability.
- Streaming & Real‑Time Processing: Build and maintain real‑time data streams using Kafka, Pub/Sub, and Flink, enabling low‑latency analytics for dynamic retail scenarios.
- Collaboration & Stakeholder Engagement: Partner with data scientists, business analysts, and product owners to translate business requirements into technical specifications and deliver end‑to‑end solutions.
- Performance Optimization: Conduct profiling, tuning, and cost‑optimization of data pipelines to meet SLAs and reduce cloud spend.
- Code Quality & Documentation: Write clean, testable code, maintain comprehensive documentation, and contribute to shared libraries and best‑practice repositories.
- Mentorship & Leadership: Guide junior engineers, conduct code reviews, and foster a culture of continuous improvement and knowledge sharing.
- Innovation & Continuous Learning: Stay abreast of emerging data technologies, propose proof‑of‑concepts, and champion adoption of modern data engineering practices.
Essential Qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
- 3+ years of professional experience designing and operating large‑scale data pipelines in a cloud environment (GCP, AWS, or Azure).
- Proficiency in at least one programming language such as Python, Scala, or Java, with a strong emphasis on data‑centric development.
- Hands‑on experience with Hadoop ecosystem tools (Hive, HBase), Spark, and distributed computing platforms.
- Solid understanding of relational databases (MySQL, PostgreSQL) and NoSQL technologies (MongoDB, Cassandra, or similar).
- Experience with data warehousing solutions (BigQuery, Snowflake, Redshift) and BI tools (Looker, Tableau, Power BI).
- Familiarity with workflow orchestration tools such as Apache Airflow, Automic, or similar.
- Demonstrated ability to design data models, write efficient SQL, and implement data validation frameworks.
Preferred Qualifications & Nice‑to‑Have Skills
- Experience with Databricks, Delta Lake, or other modern lakehouse architectures.
- Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for data engineering.
- Exposure to machine learning pipelines and feature engineering workflows.
- Certifications in cloud platforms (e.g., Google Cloud Professional Data Engineer).
- Strong problem‑solving abilities, creativity, and a data‑first mindset.
- Excellent communication skills, with the ability to convey technical concepts to non‑technical stakeholders.
Core Skills & Competencies
- Technical Acumen: Deep expertise in data engineering frameworks, cloud services, and programming languages.
- Analytical Thinking: Ability to dissect complex business problems, translate them into data solutions, and evaluate outcomes.
- Collaboration: Proven track record of working in cross‑functional teams, building consensus, and delivering results.
- Adaptability: Comfort with fast‑paced environments, shifting priorities, and evolving technology stacks.
- Leadership: Experience mentoring junior engineers and fostering a culture of best practices.
- Customer Focus: Commitment to delivering data products that directly improve merchant and shopper experiences.
Career Growth & Learning Opportunities
At careerzynith, your career trajectory is driven by your ambition and the impact you create. As a Senior Data Engineer, you will have access to:
- Mentorship from industry veterans and participation in internal tech‑talks and hackathons.
- Funding for certifications, conferences, and advanced coursework in data science, cloud architecture, and AI.
- Opportunities to lead high‑visibility projects that influence the strategic direction of careerzynith’s retail platform.
- Clear pathways to senior technical leadership roles (e.g., Lead Data Engineer, Data Architecture Manager) or product‑focused positions (e.g., Data Product Owner).
Work Environment & Culture
careerzynith embraces a flexible, hybrid work model that blends remote productivity with collaborative in‑person sessions at our innovation hubs. Our culture is built on:
- Inclusivity: A commitment to diversity, equity, and inclusion where every voice is valued.
- Innovation: Encouragement to experiment, fail fast, and iterate on ideas that drive business value.
- Transparency: Open communication channels with leadership, clear roadmaps, and regular feedback loops.
- Well‑Being: Programs that support mental health, work‑life balance, and personal growth.
Compensation, Perks & Benefits
careerzynith offers a competitive total rewards package that includes:
- Base salary ranging from $70,000 to $80,000 annually, commensurate with experience.
- Performance‑based bonuses and incentive programs.
- Comprehensive health, dental, and vision coverage.
- 401(k) matching, stock purchase plan, and equity participation.
- Generous paid time off, parental leave, and flexible holiday policies.
- Professional development stipend, tuition reimbursement, and access to online learning platforms.
- Wellness programs, virtual fitness classes, and employee assistance resources.
How to Apply
If you are passionate about turning massive data sets into strategic assets and thrive in a collaborative, forward‑thinking environment, we want to hear from you. To apply:
- Prepare your résumé, a cover letter highlighting relevant experience, and copies of your degree certificates.
- Visit the application portal here and complete the online form.
- Upload your supporting documents (transcripts, passport‑size photo, and signature).
- Submit your application and await a response from our recruiting team.
Join careerzynith – Make an Impact at Scale
At careerzynith, your work will touch the lives of millions of shoppers and merchants across the globe. By building reliable data pipelines and delivering actionable insights, you will directly influence the future of retail, technology, and customer experience. Take the next step in your career and become part of a purpose‑driven organization where innovation meets impact.