Senior Big Data Engineer – Remote Data Platform Development, Cloud Integration & Machine Learning Solutions at careerzynith
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About careerzynith
careerzynith is a global leader in financial services technology, delivering innovative digital experiences to millions of customers worldwide. Our mission is to empower people to manage their finances with confidence, using cutting‑edge data platforms, AI‑driven insights, and secure cloud infrastructure. As a forward‑thinking organization, careerzynith invests heavily in emerging technologies, open‑source collaboration, and continuous learning, ensuring that every employee has the tools and support needed to thrive in a rapidly evolving industry.
Why This Role Matters
As a member of the Data Engineering & Analytics team, you will be at the heart of careerzynith’s data‑driven transformation. You will design, build, and scale massive data pipelines that power real‑time analytics, fraud detection, personalized recommendations, and strategic decision‑making across the company. Your work will directly impact the experience of millions of users, helping careerzynith stay ahead of market trends and regulatory requirements.
Key Responsibilities
Architect, develop, and maintain robust, high‑performance data pipelines using Hadoop, Spark, Hive, and related big‑data technologies.
Collaborate with product owners, data scientists, and software engineers to translate business requirements into scalable data solutions.
Lead code reviews, enforce best practices, and champion continuous integration/continuous deployment (CI/CD) pipelines for data workloads.
Automate testing, monitoring, and alerting for data jobs in development, staging, and production environments.
Identify performance bottlenecks, troubleshoot complex data processing issues, and implement optimizations to meet latency and throughput targets.
Mentor junior engineers, fostering a culture of knowledge sharing, agile delivery, and technical excellence.
Drive innovation by evaluating emerging technologies (e.g., cloud data warehouses, streaming platforms, machine‑learning pipelines) and recommending strategic adoption.
Document architecture decisions, data models, and operational procedures to ensure maintainability and compliance.
Participate in on‑call rotations and incident response, providing rapid resolution for critical data platform incidents.
Essential Qualifications
Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field (or equivalent practical experience).
3+ years of hands‑on experience in big‑data development, with a proven track record of delivering production‑grade data pipelines.
Deep expertise in Hadoop ecosystem components (HDFS, YARN, Hive, Spark, MapReduce) and proficiency in SQL‑based processing (HiveQL, Spark‑SQL, PySpark DataFrames).
Strong programming skills in Java, Python, or Scala, with an emphasis on clean, maintainable code.
Solid understanding of data‑warehousing concepts, dimensional modeling, and ETL best practices.
Experience working in Linux/UNIX environments and scripting with Bash or similar shells.
Familiarity with version control systems (GitHub, Bitbucket) and CI/CD tools (Jenkins, GitLab CI, Azure Pipelines).
Excellent problem‑solving abilities, with a data‑first mindset and the capacity to translate ambiguous requirements into concrete technical solutions.
Preferred Qualifications & Skills
Hands‑on experience with cloud platforms such as Google Cloud Platform (GCP) or Amazon Web Services (AWS), including services like BigQuery, Redshift, Dataflow, or EMR.
Knowledge of micro‑services architecture and containerization technologies (Docker, Kubernetes) for deploying data services.
Experience building streaming pipelines using Apache Kafka, Kinesis, or similar technologies.
Familiarity with NoSQL databases (HBase, Cassandra, MongoDB, Couchbase) and their integration with batch processing frameworks.
Exposure to machine‑learning workflows, data science tooling, and model deployment pipelines.
Strong communication skills, with the ability to articulate technical concepts to non‑technical stakeholders.
Demonstrated leadership experience, such as leading a small team of engineers or coordinating cross‑functional scrum teams.
Core Competencies
Analytical Thinking: Ability to dissect complex data problems, identify root causes, and propose efficient solutions.
Collaboration: Works effectively with product, analytics, and security teams to deliver integrated outcomes.
Adaptability: Thrives in a fast‑paced environment, quickly learning new technologies and adjusting to shifting priorities.
Quality Focus: Commitment to writing testable, well‑documented code and maintaining high standards for data integrity.
Innovation: Proactively explores new tools and methodologies to keep careerzynith’s data platform at the cutting edge.
Career Growth & Learning Opportunities
careerzynith believes that employee development is a strategic advantage. In this role, you will have access to:
Annual learning stipend for conferences, certifications, or online courses (e.g., Cloudera, AWS, GCP, Coursera).
Mentorship programs pairing you with senior architects and data science leaders.
Opportunities to contribute to open‑source projects and internal innovation labs.
Clear career pathways from Senior Engineer to Lead Engineer, Data Platform Architect, and eventually Director of Data Engineering.
Cross‑functional rotations that expose you to product management, security, and compliance domains.
Work Environment & Culture at careerzynith
Our remote‑first culture is built on trust, autonomy, and collaboration. Whether you are based in Phoenix, USA, or anywhere else in the world, you will enjoy:
Flexible working hours that respect work‑life balance.
A supportive, inclusive community that celebrates diverse perspectives.
Regular virtual coffee chats, hackathons, and team‑building events.
State‑of‑the‑art collaboration tools (Slack, Microsoft Teams, Confluence) to keep you connected.
Access to a secure, high‑performance development environment with VPN, cloud resources, and ergonomic home‑office allowances.
Compensation, Perks & Benefits
careerzynith offers a competitive compensation package that reflects your expertise and the market demand for big‑data talent. While the base rate for this role is $28 per hour, total rewards include:
Performance‑based bonuses and annual salary reviews.
Comprehensive health, dental, and vision insurance plans.
Retirement savings options with company matching.
Generous paid time off, parental leave, and sick days.
Wellness programs, including virtual fitness classes and mental‑health resources.
Technology stipend for home‑office equipment, high‑speed internet, and ergonomic accessories.
Employee assistance program and financial counseling services.
How to Apply
If you are passionate about building data platforms that power the next generation of financial services, we want to hear from you. Join careerzynith’s #Teamcareerzynith and help shape a data‑centric future.
Apply Now
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Apply for this job
About careerzynith
careerzynith is a global leader in financial services technology, delivering innovative digital experiences to millions of customers worldwide. Our mission is to empower people to manage their finances with confidence, using cutting‑edge data platforms, AI‑driven insights, and secure cloud infrastructure. As a forward‑thinking organization, careerzynith invests heavily in emerging technologies, open‑source collaboration, and continuous learning, ensuring that every employee has the tools and support needed to thrive in a rapidly evolving industry.
Why This Role Matters
As a member of the Data Engineering & Analytics team, you will be at the heart of careerzynith’s data‑driven transformation. You will design, build, and scale massive data pipelines that power real‑time analytics, fraud detection, personalized recommendations, and strategic decision‑making across the company. Your work will directly impact the experience of millions of users, helping careerzynith stay ahead of market trends and regulatory requirements.
Key Responsibilities
Architect, develop, and maintain robust, high‑performance data pipelines using Hadoop, Spark, Hive, and related big‑data technologies.
Collaborate with product owners, data scientists, and software engineers to translate business requirements into scalable data solutions.
Lead code reviews, enforce best practices, and champion continuous integration/continuous deployment (CI/CD) pipelines for data workloads.
Automate testing, monitoring, and alerting for data jobs in development, staging, and production environments.
Identify performance bottlenecks, troubleshoot complex data processing issues, and implement optimizations to meet latency and throughput targets.
Mentor junior engineers, fostering a culture of knowledge sharing, agile delivery, and technical excellence.
Drive innovation by evaluating emerging technologies (e.g., cloud data warehouses, streaming platforms, machine‑learning pipelines) and recommending strategic adoption.
Document architecture decisions, data models, and operational procedures to ensure maintainability and compliance.
Participate in on‑call rotations and incident response, providing rapid resolution for critical data platform incidents.
Essential Qualifications
Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field (or equivalent practical experience).
3+ years of hands‑on experience in big‑data development, with a proven track record of delivering production‑grade data pipelines.
Deep expertise in Hadoop ecosystem components (HDFS, YARN, Hive, Spark, MapReduce) and proficiency in SQL‑based processing (HiveQL, Spark‑SQL, PySpark DataFrames).
Strong programming skills in Java, Python, or Scala, with an emphasis on clean, maintainable code.
Solid understanding of data‑warehousing concepts, dimensional modeling, and ETL best practices.
Experience working in Linux/UNIX environments and scripting with Bash or similar shells.
Familiarity with version control systems (GitHub, Bitbucket) and CI/CD tools (Jenkins, GitLab CI, Azure Pipelines).
Excellent problem‑solving abilities, with a data‑first mindset and the capacity to translate ambiguous requirements into concrete technical solutions.
Preferred Qualifications & Skills
Hands‑on experience with cloud platforms such as Google Cloud Platform (GCP) or Amazon Web Services (AWS), including services like BigQuery, Redshift, Dataflow, or EMR.
Knowledge of micro‑services architecture and containerization technologies (Docker, Kubernetes) for deploying data services.
Experience building streaming pipelines using Apache Kafka, Kinesis, or similar technologies.
Familiarity with NoSQL databases (HBase, Cassandra, MongoDB, Couchbase) and their integration with batch processing frameworks.
Exposure to machine‑learning workflows, data science tooling, and model deployment pipelines.
Strong communication skills, with the ability to articulate technical concepts to non‑technical stakeholders.
Demonstrated leadership experience, such as leading a small team of engineers or coordinating cross‑functional scrum teams.
Core Competencies
Analytical Thinking: Ability to dissect complex data problems, identify root causes, and propose efficient solutions.
Collaboration: Works effectively with product, analytics, and security teams to deliver integrated outcomes.
Adaptability: Thrives in a fast‑paced environment, quickly learning new technologies and adjusting to shifting priorities.
Quality Focus: Commitment to writing testable, well‑documented code and maintaining high standards for data integrity.
Innovation: Proactively explores new tools and methodologies to keep careerzynith’s data platform at the cutting edge.
Career Growth & Learning Opportunities
careerzynith believes that employee development is a strategic advantage. In this role, you will have access to:
Annual learning stipend for conferences, certifications, or online courses (e.g., Cloudera, AWS, GCP, Coursera).
Mentorship programs pairing you with senior architects and data science leaders.
Opportunities to contribute to open‑source projects and internal innovation labs.
Clear career pathways from Senior Engineer to Lead Engineer, Data Platform Architect, and eventually Director of Data Engineering.
Cross‑functional rotations that expose you to product management, security, and compliance domains.
Work Environment & Culture at careerzynith
Our remote‑first culture is built on trust, autonomy, and collaboration. Whether you are based in Phoenix, USA, or anywhere else in the world, you will enjoy:
Flexible working hours that respect work‑life balance.
A supportive, inclusive community that celebrates diverse perspectives.
Regular virtual coffee chats, hackathons, and team‑building events.
State‑of‑the‑art collaboration tools (Slack, Microsoft Teams, Confluence) to keep you connected.
Access to a secure, high‑performance development environment with VPN, cloud resources, and ergonomic home‑office allowances.
Compensation, Perks & Benefits
careerzynith offers a competitive compensation package that reflects your expertise and the market demand for big‑data talent. While the base rate for this role is $28 per hour, total rewards include:
Performance‑based bonuses and annual salary reviews.
Comprehensive health, dental, and vision insurance plans.
Retirement savings options with company matching.
Generous paid time off, parental leave, and sick days.
Wellness programs, including virtual fitness classes and mental‑health resources.
Technology stipend for home‑office equipment, high‑speed internet, and ergonomic accessories.
Employee assistance program and financial counseling services.
How to Apply
If you are passionate about building data platforms that power the next generation of financial services, we want to hear from you. Join careerzynith’s #Teamcareerzynith and help shape a data‑centric future.
Apply Now
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Apply for this job