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About careerzynith
careerzynith is a global leader in retail technology, empowering millions of shoppers worldwide through innovative data‑driven solutions. Our mission is to transform the retail experience by turning massive data sets into actionable insights that improve customer lives, streamline operations, and drive sustainable growth. As part of the careerzynith family, you will join a diverse, inclusive community that values curiosity, collaboration, and continuous learning. Whether you are a seasoned data professional or an emerging talent, careerzynith offers a platform where your ideas can shape the future of retail.
Role Overview
We are seeking a highly motivated Senior Data Engineer to design, build, and maintain robust data pipelines that power our retail analytics ecosystem. This remote position (based in California) will work closely with data scientists, analysts, product managers, and engineering teams to ensure that data flows seamlessly from source to insight. You will be responsible for translating complex business problems into scalable data solutions, maintaining data quality, and driving continuous improvement across the data lifecycle.
Key Responsibilities
- Data Ingestion & Transformation: Consolidate data from multiple heterogeneous sources, design efficient ETL/ELT pipelines, and apply best‑in‑class data modeling techniques to create clean, curated datasets ready for analysis.
- Data Architecture & Modeling: Develop logical and physical data models, including dimensional, relational, and NoSQL schemas, that support both operational reporting and advanced analytics.
- Pipeline Automation & Orchestration: Implement end‑to‑end workflow automation using tools such as Airflow, Prefect, or Automic, ensuring reliable scheduling, monitoring, and alerting.
- Performance Optimization: Conduct root‑cause analysis of pipeline bottlenecks, tune queries, and leverage distributed processing frameworks (e.g., Spark, Flink) to achieve sub‑second latency where required.
- Data Quality & Governance: Define and enforce data quality rules, implement data profiling, and collaborate with data stewards to maintain compliance with governance policies.
- Collaboration & Communication: Partner with data scientists to understand model requirements, work with product owners to prioritize features, and mentor junior engineers on best practices.
- Documentation & Knowledge Sharing: Produce clear technical documentation, maintain architecture diagrams, and contribute to internal knowledge bases and playbooks.
- Innovation & Continuous Improvement: Stay abreast of emerging technologies (e.g., DataBricks, Snowflake, Kafka), propose proof‑of‑concepts, and drive adoption of modern data stack components.
- Business Insight Generation: Translate business objectives into data solutions, build cost‑benefit analyses for new initiatives, and present findings to senior leadership.
- Support & Incident Management: Participate in on‑call rotations, troubleshoot production incidents, and implement post‑mortem processes to prevent recurrence.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
- Minimum 3‑5 years of professional experience designing and operating large‑scale data pipelines in a cloud environment.
- Proficiency in at least one programming language such as Python, Scala, or Java, with a strong emphasis on clean, maintainable code.
- Hands‑on experience with distributed computing platforms (e.g., Apache Spark, Hadoop) and cloud services (e.g., Google Cloud Platform, AWS, Azure).
- Solid understanding of data modeling concepts, including star/snowflake schemas, OLAP cubes, and NoSQL data stores.
- Experience with streaming technologies such as Apache Kafka, Pub/Sub, or Kinesis.
- Familiarity with orchestration tools like Airflow, Prefect, or Automic for workflow management.
- Strong analytical mindset with the ability to translate ambiguous business problems into concrete technical solutions.
- Excellent written and verbal communication skills, capable of articulating complex ideas to both technical and non‑technical audiences.
Preferred Qualifications
- Master’s degree or advanced certifications in data engineering, big data, or cloud architecture.
- Experience with modern data warehousing solutions such as Snowflake, BigQuery, or Redshift.
- Knowledge of DataBricks or similar unified analytics platforms.
- Exposure to BI tools (e.g., Looker, Tableau, Power BI) and the ability to support self‑service analytics.
- Hands‑on experience with NoSQL databases like MongoDB, Cassandra, or DynamoDB, as well as relational databases such as MySQL, PostgreSQL.
- Demonstrated track record of mentoring junior engineers and leading cross‑functional project teams.
- Experience implementing data security and privacy controls in compliance with GDPR, CCPA, or similar regulations.
Core Skills & Competencies
- Technical Acumen: Deep expertise in data pipeline construction, cloud-native services, and performance tuning.
- Problem‑Solving: Ability to dissect complex data challenges, propose innovative solutions, and iterate quickly.
- Collaboration: Strong team player who thrives in a matrixed environment, building relationships across product, analytics, and operations.
- Adaptability: Comfortable working in a fast‑paced, ever‑changing landscape; eager to learn new tools and methodologies.
- Business Insight: Understanding of retail operations, supply chain dynamics, and customer behavior to align data initiatives with strategic goals.
- Leadership: Proactive in driving technical standards, code reviews, and continuous integration/continuous deployment (CI/CD) practices.
Career Development & Learning Opportunities
At careerzynith, your growth is a priority. You will have access to:
- Mentorship programs pairing you with senior architects and industry experts.
- Annual learning stipend for conferences, certifications, or online courses.
- Internal hackathons and innovation labs where you can prototype cutting‑edge ideas.
- Clear career pathways from Data Engineer to Lead Engineer, Data Platform Manager, or Architecture Specialist.
- Rotational assignments across different business units, giving you a holistic view of the retail ecosystem.
Culture & Work Environment
careerzynith fosters an inclusive, flexible, and collaborative culture. Our remote‑first policy means you can work from anywhere in California while still feeling connected through virtual “collaboration hubs,” regular video‑check‑ins, and quarterly in‑person meet‑ups at our innovation centers. We celebrate diversity, encourage open dialogue, and support work‑life balance through generous PTO, flexible hours, and wellness programs.
Compensation, Perks & Benefits
We offer a competitive total rewards package that includes:
- Base salary ranging from $70,000 to $80,000 annually, commensurate with experience.
- Performance‑based bonuses and stock‑option grants.
- Comprehensive health, dental, and vision coverage.
- 401(k) plan with company match and employee stock purchase program.
- Paid parental leave, family care assistance, and flexible work schedules.
- Wellness stipend, mental‑health resources, and employee assistance programs.
- Professional development budget and tuition reimbursement.
- Access to cutting‑edge technology, cloud credits, and a collaborative learning environment.
How to Apply
If you are ready to make a tangible impact on the future of retail data, follow these steps:
- Prepare the required documents: a copy of your degree certificate with transcripts, a recent passport‑size photograph, and a digital signature.
- Visit the official application portal (link provided below) and complete the online form.
- Upload your resume, cover letter, and the supporting documents listed above.
- Submit your application and await a confirmation email with next steps.
We review applications on a rolling basis, so early submission is encouraged.
Join the careerzynith Team
At careerzynith, your work will directly influence the shopping experience of millions of customers worldwide. If you thrive on turning raw data into strategic advantage, love solving intricate technical puzzles, and want to grow within a forward‑thinking organization, we want to hear from you. Apply today and become part of a team that is redefining retail through data excellence.
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