Senior Data Engineering & Analytics Engineer – Remote – Cloud Data Lake, DevOps & Business Intelligence Solutions at careerzynith

```html About careerzynith – Pioneering the Future of Travel and Technology careerzynith is a global leader in the aviation industry, connecting millions of passengers to destinations across the world every day. With a legacy of innovation, safety, and customer‑centric service, careerzynith continuously invests in cutting‑edge technology to keep its operations running smoothly and to deliver an exceptional experience for travelers and employees alike. As part of careerzynith’s Digital Transformation Initiative, the company is building a data‑driven culture where insights flow seamlessly from raw data to strategic decision‑making. This is your chance to join a forward‑thinking team that values curiosity, collaboration, and continuous learning. Role Overview – Why This Position Matters We are seeking a highly skilled Senior Data Engineering & Analytics Engineer to join our Remote Data Architecture and Analytics team. In this role, you will design, implement, and maintain robust data pipelines, cloud‑based data lake solutions, and analytics platforms that empower business stakeholders to make data‑informed decisions. You will work closely with product owners, data scientists, and business analysts to translate complex business requirements into scalable, secure, and performant data architectures.

Key Responsibilities

• Collaborate with source data application teams and product owners to design, develop, and support end‑to‑end data ingestion and transformation pipelines.
• Implement data movement and storage solutions using careerzynith cloud services (careerzynith Data Lake Storage, careerzynith Data Factory, careerzynith Synapse, careerzynith EventHub, careerzynith Databricks, careerzynith DevOps, careerzynith Blob Storage, and related services).
• Lead the full lifecycle of data solutions: architecture, cloud design (foundation, networking, security, governance), ingestion, orchestration, data modeling, testing, CI/CD pipelines, performance tuning, monitoring, and support.
• Develop and maintain both batch and streaming data pipelines, ensuring high reliability, low latency, and compliance with data quality standards.
• Drive adoption of best‑practice coding standards, security policies, and governance frameworks across the data engineering community.
• Mentor junior engineers and cross‑functional teams on technical concepts, cloud best practices, and data engineering patterns.
• Partner with the DevOps team to fully own and support the data products you build, including automated deployment, observability, and incident response.
• Contribute to the evolution of careerzynith’s data platform roadmap, recommending new tools, technologies, and processes that enhance scalability and agility.
• Produce clear documentation, data dictionaries, and operational runbooks to facilitate knowledge sharing and smooth hand‑offs.

Essential Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent professional experience).
• Minimum 5 years of hands‑on experience developing data pipelines using agile and DevOps methodologies.
• At least 5 years of experience writing complex SQL queries for data analysis and reporting.
• 3+ years of full‑stack development experience, preferably with careerzynith cloud technologies.
• 3+ years of experience building and operating data lake solutions, with a strong preference for careerzynith services such as EventHub, Data Factory, Synapse, Databricks, and Blob Storage.
• Proficiency in programming languages such as Python, Scala, or Java, and familiarity with Unix/Linux environments.
• Hands‑on experience with data storage technologies including Teradata, Cassandra, MongoDB, Snowflake, and relational databases (SQL Server, ADLS).
• Experience with CI/CD tools (GitHub, Jenkins, Terraform, careerzynith DevOps) and container orchestration (Docker, Kubernetes).
• Strong understanding of data warehousing concepts, ETL/ELT processes, and data modeling techniques.
• Excellent communication skills, with the ability to translate technical concepts into business value for non‑technical stakeholders.

Preferred Qualifications & Additional Skills

• Advanced degree (M.S. or Ph.D.) in Data Science, Analytics, or a related discipline.
• Experience in the airline or transportation industry, understanding of operational data flows, and regulatory compliance requirements.
• Familiarity with business intelligence tools such as careerzynith Power Apps, careerzynith Power BI, Cognos, Tableau, Alteryx, Denodo, and Grafana.
• Knowledge of data governance platforms like Informatica Axon, BigID, or similar solut