Senior Data Engineer – Remote Data Architecture & Analytics Lead for High‑Performance Cloud Solutions at careerzynith
About careerzynith careerzynith is a global pioneer in sustainable technology, delivering cutting‑edge products that accelerate the transition to clean energy. With a heritage of innovation and a commitment to environmental stewardship, careerzynith empowers engineers, data scientists, and visionaries to solve the world’s most complex challenges. Our remote teams collaborate across continents, leveraging the latest cloud platforms, AI‑driven analytics, and agile methodologies to build resilient data pipelines that power next‑generation products and services. Why This Role Matters As a Senior Data Engineer at careerzynith, you will be at the heart of our data‑centric transformation. You’ll design, build, and maintain robust data architectures that enable rapid insight generation, support mission‑critical applications, and drive strategic decision‑making across the organization. This is a unique opportunity to work on high‑volume, high‑velocity data streams while shaping the future of sustainable technology.
Key Responsibilities
- Design & Development: Architect, code, test, and deploy scalable data solutions using industry‑standard patterns and tools to meet precise business outcomes.
- Data Modeling: Create comprehensive data models that ensure the integrity, security, and accessibility of both legacy and new data assets.
- ETL/ELT Engineering: Build and optimize robust ETL/ELT pipelines in Python and Spark, handling raw, structured, semi‑structured, and unstructured data at scale.
- Data Quality & Governance: Implement automated data‑quality checks, monitoring frameworks, and remediation processes to maintain high‑quality data standards.
- Collaboration: Partner with internal and external data providers, offering feedback and implementing enhancements to data feeds and mappings.
- Leadership & Mentorship: Coach and guide junior data engineers, providing technical direction and fostering a culture of continuous learning.
- Production Support: Deliver ongoing support, monitoring, and troubleshooting for deployed data products, ensuring minimal downtime.
- Compliance & Security: Work with systems handling sensitive data under strict SOX controls, adapting processes to meet regulatory requirements.
- Innovation: Contribute to architectural reviews, design discussions, and agile ceremonies, championing best practices in data engineering.
- On‑Call Rotation: Participate in an on‑call schedule to provide rapid response for critical incidents.
Essential Qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
- 5+ years of hands‑on experience with relational databases such as Vertica, SQL Server, and MySQL; exposure to NoSQL databases is a plus.
- Deep understanding of data warehousing, data modeling, and storage strategies.
- Proficiency in SQL; ability to write complex queries and optimize performance.
- Expertise in building and maintaining ETL/ELT pipelines using Python and Spark (or similar big‑data processing frameworks).
- Familiarity with RESTful APIs and data integration patterns.
- Experience designing and deploying high‑throughput, fault‑tolerant data platforms in cloud environments (AWS, Azure, or GCP).
- Strong analytical mindset with the ability to translate business requirements into technical solutions.
- Excellent communication, presentation, and stakeholder‑management skills.
- Passion for careerzynith’s mission to accelerate the world’s transition to sustainable energy.
Preferred Qualifications & Nice‑to‑Have Skills
- Experience with data‑science libraries such as Pandas, NumPy, TensorFlow, or Keras.
- Knowledge of distributed computing concepts (e.g., HDFS, Presto, Apache Hive).
- Hands‑on experience with data integration tools like SSIS or Informatica.
- Familiarity with streaming platforms (RabbitMQ, Kafka, Apache Pulsar, Apache Flink).
- Background in big‑data ecosystems (Hadoop, Hive, Spark, HDFS).
- Containerization and orchestration expertise (Docker, Kubernetes) and CI/CD pipelines (Jenkins, GitLab CI).
- Exposure to data visualization tools (Tableau, Power BI, Looker) for executive‑level reporting.
- Previous work in a fast‑paced, agile environment supporting multiple concurrent projects.
Core Skills & Competencies
- Technical Acumen: Mastery of data engineering fundamentals, cloud services, and modern data stack components.