Role Description We are seeking an experienced Senior Software Engineer, Data Platform, to contribute to the design, development, and optimization of our data infrastructure. This role requires deep expertise in GCP, data engineering, Change Data Capture (CDC), ETL, governance, and streaming technologies. You will work closely with data scientists, analysts, and software engineers to ensure seamless data ingestion, processing, and access across the organization. This is a foundational role within a growing team that requires a hands-on architect who can balance speed, excellence, and pragmatism. Key Responsibilities - Contribute to the design, development, and scaling of core data infrastructure using GCP, Spark, Databricks, and Fivetran. - Develop robust and maintainable ETL/ELT workflows that support diverse structured and unstructured data needs across the organization. - Implement and manage Change Data Capture (CDC) pipelines to enable near real-time data replication and synchronization. - Define and enforce data governance and compliance standards, including access control, auditability, lineage, and metadata management. - Build and manage streaming and batch data pipelines to serve high-impact use cases across analytics, product, compliance, and experimentation. - Act as a strategic partner to cross-functional teams (product, analytics, engineering, clinical) to ensure data is accessible, trustworthy, and impactful. - Drive the long-term architectural vision of our data platform to support current and future business and product needs. Qualifications - 5+ years of experience in software engineering, with a focus on scalable data architectures. - Strong expertise in GCP (IAM, GCS, Pub/Sub, etc.) and hands-on experience with Spark and Databricks. - Hands-on experience with CDC technologies like Fivetran, or equivalent. - Proficiency in ETL/ELT tools and frameworks (dbt, Apache Airflow, Dataform, etc.). - Deep understanding of data governance principles, including compliance and security best practices. - Demonstrated success in collaborating across functions to deliver data solutions for analytics, experimentation, or compliance. - A balance of IC execution and leadership skills; you’re equally comfortable rolling up your sleeves or mentoring others. - Familiarity with streaming data architecture, real-time ingestion, and delivery frameworks. - Proficient in SQL and Python for data processing and automation. - Strong problem-solving skills with the ability to work in a fast-paced environment. - Excellent communication and technical storytelling skills — you can align technical work with business value. Nice-to-Have Skills and Experiences - Experience with Terraform or Infrastructure-as-Code (IaC) for data infrastructure automation. - Background in HIPAA or other regulated environments with sensitivity to data privacy and compliance. - Familiarity with the dbt Semantic Layer and modern data modeling best practices. - Exposure to data observability platforms and practices. - Familiarity with machine learning data pipelines. - Exposure to multi-cloud or hybrid-cloud environments. - Experience building scalable solutions in a 0-1 environment. To be a strong fit, you also need - Bias Toward Action: Demonstrated ability to take initiative, make decisions under uncertainty, and move projects forward even in the face of ambiguity. - Entrepreneurial Spirit: Strong adaptability to changing business needs with a knack for building and optimizing processes. - Communication: Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders. - Remote Work Adaptability: Comfort with remote work environments, demonstrating the ability to stay productive and connected with the team irrespective of physical location. - Continuous Improvement: A willingness to question assumptions and a commitment to continuous improvement. Benefits - Competitive salary. - Equity and benefits package. - Flexible, fully-remote working hours. - A dynamic work environment where creativity and innovation are encouraged.

• Lead and develop two Director-level managers and their respective teams spanning data platform engineering, data pipeline development, and practitioner enablement. • Set the multi-quarter roadmap for the Enterprise Data Platform and Engineering organizations, balancing infrastructure modernization, operational stability, security, and enablement priorities. • Build a high-performance engineering culture grounded in ownership, accountability, and operational excellence. • Drive headcount planning, organizational design, and career development frameworks that attract and retain top talent across a distributed team. • Serve as a trusted partner to the VP of Engineering & Innovation, contributing to broader engineering strategy and organizational decisions. • Establish clear prioritization frameworks to manage competing demands from security, infrastructure modernization, platform stability, and practitioner tooling. • Own the strategic direction for ZoomInfo's core data infrastructure, including Snowflake, Airflow, Fivetran, AWS, and GCP. • Guide the design and buildout of an Iceberg-based GCS Data Lake as the foundation for scalable, cost-efficient storage, including governance, observability, and ingestion patterns. • Oversee cloud infrastructure consolidation to GCP, including Airflow 3.x upgrades, service migrations, and deprecation of legacy environments. • Drive SaaS vendor strategy and cost optimization — evaluating build-vs-buy decisions for ingestion (Fivetran/Airbyte), cost management, and other platform tooling. • Oversee monorepo consolidation and CI/CD standardization to enable consistent governance and accelerate deployment velocity. • Ensure the platform team maintains a strong security posture including service account modernization, key rotation, legacy role decommissioning, access reviews, and incident response readiness. • Oversee the development, reliability, and monitoring of all enterprise data pipelines powering analytics, reporting, and operational workflows. • Guide the evolution of data modeling practices through dbt and semantic models, ensuring data products are trusted, documented, and well-tested. • Champion the shift-left initiative, enabling product and engineering domain teams to own their data assets end-to-end while maintaining quality and standards. • Support the development of AI-assisted tooling (agents and micro apps) that automate data engineering workflows — from ingestion and modeling to deployment and monitoring. • Drive platform-wide data standards alignment for metadata, ownership, testing, and documentation.

Title: Staff Data Engineer Location: Bengaluru, India Job Description: About EarnIn As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks. We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey. POSITION SUMMARY We are looking for an experienced Staff Data Engineer proficient in Data infrastructure operations, automation, and management, as well as traditional data engineering responsibilities. As a Staff Data Engineer, you will work cross-functionally with various teams and contribute to helping build an enterprise-grade Data Platform. This position will be hybrid from our Bengaluru office, as part of our expanding site, with 2+ days in the office. EarnIn provides excellent employee benefits, including healthcare, internet/cell phone reimbursement, a learning and development stipend, and opportunities to collaborate with and travel to our Mountain View HQ and Bangkok Site. Our salary ranges are determined by role, level, and location. WHAT YOU'LL DO - Lead and focus on scaling the data infrastructure, streamlining the data delivery, and designing and implementing AI automation to replace manual operations. - Engage closely with a wide array of stakeholders, including executive, product, data, and design teams, providing high-level support for data infrastructure challenges, advising on technical data issues, and implementing self-serve solutions. - Develop sophisticated AI-based analytical tools that integrate with the data pipeline to provide deep insights into key business metrics, including customer growth and operational efficiency. - Architect and manage extensive, sophisticated data sets to meet complex business needs and requirements. - Engage closely with a wide array of stakeholders, including executive, product, data, and design teams, providing high-level support for data infrastructure challenges and advising on technical data issues. - Make a meaningful impact on the lives of our community members. - Collaborate and mentor other senior engineers while providing thoughtful guidance using code, design, and architecture reviews. - Contribute to defining technical direction, planning the roadmap, escalating issues, and synthesizing feedback to ensure team success. - Estimate and manage team project timelines and risks. - Participate in hiring and onboarding for new team members. - Lead cross-team engineering initiatives. - Constantly learning about new technologies and industry standards in data engineering. WHAT WE'RE LOOKING FOR - 7+ years in designing, building, and maintaining the Data infrastructure, and the ability to lead complex projects and teams. - Bachelor's, Master’s, or PhD degree in computer science, computer engineering, or a related technical discipline, or equivalent industry experience. - Deep knowledge of Kafka, Proficiency in programming languages like Python and Scala, and a good understanding of ML engineering. - Strong knowledge of distributed computing frameworks, such as Apache Spark, with cloud platforms such as AWS, Azure, or GCP. - Working experience with Databricks would be nice to have - Experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, ChatGPT, or similar tools) as part of your software development workflow - Deep understanding of database design, SQL, and NoSQL databases. Experience in managing large datasets and optimizing database performance. - Proficiency in Git and Terraform, and experience in deploying continuous integration and continuous deployment (CI/CD) practices. - Experience in managing event-driven systems, particularly with Kafka in cloud environments. - Expertise in developing and implementing data governance frameworks, policies, and procedures to ensure data quality, compliance, and effective data management practices. - Deep understanding of data security principles, including encryption, decryption, and secure data storage and transfer protocol # LI-Hybrid At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant. EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.

• Desarrollar scripts Python para automatización, limpieza y validación de datos. • Colaborar con el BA para entender las reglas de negocio contable. • Monitorear y optimizar el rendimiento de los jobs Spark en producción. • Documentar los flujos de datos, modelos y diccionarios de datos.