Why talentflow?
talentflow is a global leader in financial technology and digital transformation, empowering millions of consumers and businesses with secure, innovative solutions. As a forward‑thinking organization, talentflow invests heavily in cutting‑edge data platforms, artificial intelligence, and cloud‑native architectures to stay ahead of the rapidly evolving fintech landscape. Our mission is to turn data into actionable insight, delivering seamless experiences that drive growth, trust, and financial inclusion worldwide. Joining talentflow means becoming part of a culture that celebrates curiosity, collaboration, and continuous learning—where every line of code you write contributes to a larger purpose.
Core Information
- Location: Remote (U.S. based, with a preference for candidates in the Phoenix, AZ time zone)
- Compensation: Competitive hourly rate ($20‑$30 per hour) plus performance bonuses and equity participation
- Position: Senior Big Data Engineer – Remote
- Start Date: Immediate openings – we are hiring now!
- Company: talentflow
- Employment Type: Full‑time, 40‑hour week
- Work Hours: Flexible schedule with core collaboration hours (8 AM – 4 PM PT)
Job Summary
talentflow is seeking a highly motivated, technically proficient Senior Big Data Engineer to join our fast‑moving, agile data engineering team. In this role, you will design, build, and maintain large‑scale data pipelines that ingest, process, and transform massive volumes of transactional and behavioral data. You will collaborate closely with data scientists, product managers, and business analysts to deliver robust, low‑latency analytics solutions that power real‑time fraud detection, personalized offers, and strategic decision‑making across the organization.
Key Responsibilities
- Architect and develop end‑to‑end data pipelines using Hadoop, Spark, Hive, and PySpark to move terabytes of data from source systems into our data lake and warehouse.
- Design scalable data models that support both batch and streaming workloads, ensuring high performance for downstream analytics and machine‑learning workloads.
- Implement data quality frameworks that include automated testing, schema validation, and anomaly detection to guarantee data integrity.
- Collaborate with cross‑functional agile squads to translate business requirements into technical specifications, user stories, and acceptance criteria.
- Lead code reviews and mentor junior engineers, fostering a culture of clean code, continuous improvement, and shared ownership.
- Optimize SQL and Spark queries for cost‑efficiency and speed, reducing processing time by up to 40% through advanced indexing, partitioning, and caching strategies.
- Integrate cloud services (AWS/GCP) and container orchestration (Kubernetes) to modernize legacy workloads and enable elastic scaling.
- Maintain CI/CD pipelines using GitHub/Bitbucket, Jenkins, and GitLab CI to automate build, test, and deployment processes.
- Document technical designs, data dictionaries, and operational runbooks to ensure knowledge transfer and compliance with internal governance policies.
- Stay ahead of industry trends by researching emerging big‑data technologies, recommending proof‑of‑concepts, and driving adoption of best practices.
Essential Qualifications
- Education: Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
- Experience: Minimum 2 + years of hands‑on software development experience, with at least 2 + years focused on big‑data technologies (Hadoop, Hive, Spark, PySpark).
- Programming Skills: Proficiency in Java, Python, or Scala; strong command of UNIX/Linux shell scripting.
- Data‑Warehouse Expertise: Demonstrated experience designing and implementing data‑warehouse solutions, including dimensional modeling and ETL processes.
- SQL Mastery: Advanced knowledge of SQL, HiveQL, and Spark‑SQL, with the ability to write performant queries on massive datasets.
- Big‑Data Platforms: Hands‑on experience with Hadoop ecosystem components (HDFS, YARN, MapReduce) and Spark streaming architectures.
- Version Control & CI/CD: Proficient with Git, GitHub/Bitbucket, and continuous integration tools (Jenkins, GitLab CI, Azure DevOps).
- Analytical Mindset: Ability to translate complex business problems into scalable technical solutions, with a focus on data quality and reliability.
Preferred Qualifications & Nice‑to‑Have Skills
- Master’s degree in a quantitative discipline (Data Science, Applied Mathematics, etc.).
- Experience with cloud platforms such as Amazon Web Services (AWS) or Google Cloud Platform (GCP), especially services like EMR, Redshift, BigQuery, and Dataflow.
- Knowledge of micro‑service architecture and containerization (Docker, Kubernetes) for deploying data services.
- Familiarity with streaming technologies such as Apache Kafka, Kinesis, or Pulsar.
- Exposure to NoSQL databases (HBase, Cassandra, MongoDB, Couchbase) and their integration with batch pipelines.
- Understanding of machine‑learning pipelines and how to operationalize models using MLflow, TensorFlow Extended (TFX), or similar frameworks.
- Professional certifications (e.g., AWS Certified Big Data – Specialty, Google Professional Data Engineer, Cloudera Certified Professional).
- Strong written and verbal communication skills, with the ability to present technical concepts to non‑technical stakeholders.
Core Competencies & Skills for Success
- Problem‑Solving: Ability to dissect ambiguous requirements, identify root causes, and devise elegant, maintainable solutions.
- Collaboration: Comfortable working in a distributed, agile environment, contributing to sprint planning, stand‑ups, and retrospectives.
- Continuous Learning: Passion for staying current with the rapidly evolving big‑data ecosystem and sharing knowledge with peers.
- Attention to Detail: Meticulous approach to data validation, testing, and documentation to meet regulatory and compliance standards.
- Leadership: Proven ability to guide junior engineers, champion best practices, and influence technical direction.
- Customer‑Centric Mindset: Understanding of how data products impact end‑users, driving decisions that improve user experience and business outcomes.
Career Growth & Learning Opportunities
talentflow invests heavily in the professional development of its people. As a Senior Big Data Engineer, you will have access to:
- Annual tuition reimbursement for advanced degrees, certifications, and specialized training.
- Mentorship programs pairing you with senior architects and data science leaders.
- Internal hackathons and innovation labs where you can prototype new ideas and receive executive sponsorship.
- Opportunities to transition into lead architect, data‑platform manager, or product‑owner roles as you demonstrate impact.
- Cross‑functional rotations that expose you to data‑science, product management, and business analytics.
Work Environment & Culture at talentflow
Our remote‑first philosophy empowers you to work from anywhere in the United States while staying tightly connected to a vibrant, inclusive community. Key cultural pillars include:
- Transparency: Open communication channels, regular town‑halls, and clear roadmaps.
- Innovation: A “fail fast, learn faster” mindset that encourages experimentation.
- Diversity & Inclusion: Employee resource groups, inclusive hiring practices, and a commitment to equitable growth.
- Work‑Life Balance: Flexible schedules, generous paid‑time‑off policies, and mental‑health resources.
- Recognition: Quarterly awards, peer‑nominated accolades, and performance‑based bonuses.
Compensation, Perks & Benefits
talentflow offers a total rewards package designed to attract and retain top talent:
- Competitive hourly wage ($20‑$30) with annual salary reviews.
- Performance‑based bonuses tied to project milestones and company goals.
- Equity grants that align your success with the long‑term growth of talentflow.
- Comprehensive health, dental, and vision coverage for you and your dependents.
- 401(k) plan with company match up to 5% of salary.
- Generous paid parental leave, sick leave, and vacation accrual.
- Home‑office stipend for ergonomic equipment, high‑speed internet, and coworking space access.
- Professional development budget, conference attendance, and internal learning portals.
- Employee assistance program (EAP) for counseling, legal, and financial advice.
How to Apply
If you are excited about shaping the future of data‑driven finance, thrive in a remote, high‑impact environment, and meet the qualifications outlined above, we want to hear from you. Submit your resume, a concise cover letter highlighting your most relevant big‑data projects, and any portfolio or GitHub links that showcase your code.
Are You the One We’re Looking For?
At talentflow, we believe that great ideas come from diverse perspectives and relentless curiosity. If you have the technical chops, the collaborative spirit, and the drive to turn massive data streams into strategic advantage, apply today and become a catalyst for innovation in the fintech world.
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