- Full-time
Salary: $140,000 - 190,000 per year
Requirements:
- Minimum 8 years of extensive experience in software or data engineering within production settings
- Advanced proficiency in Java or Python, focusing on performance improvement, concurrency, and service-oriented architecture
- Significant experience in constructing scalable data pipelines using tools such as Spark, Kafka, Databricks, and Iceberg
- Solid background in RDBMS and SQL, along with practical experience with Parquet and large data file formats
- Familiarity with Hadoop ecosystems, large-scale data processing, and contemporary orchestration practices
- Hands-on expertise with cloud services such as AWS or Azure
- Experience in integrating backend services with React-based front ends (full-stack experience is a plus)
- Comprehensive knowledge of CI/CD processes, API architecture, and fundamentals of cloud infrastructure
- Bonus points for exposure to LLM/AI-based data transformation tools
- Experience with Dremio or comparable data lake query engines
- Background in highly regulated sectors, particularly finance or insurance
- Capacity to operate in hybrid or in-person environments while leading small technical teams
Responsibilities:
- Construct scalable, high-performance backend systems utilizing Java, focusing on concurrent and distributed architectures
- Design and create robust, distributed data pipelines with Spark, Databricks, Kafka, and Apache Iceberg
- Develop and manage microservices that work with both streaming and batch data inputs
- Integrate complex data systems employing ETL/ELT methodologies, Spring Expressions, and custom APIs
- Optimize and oversee datasets employing Parquet, Hadoop, and modern query layers such as Dremio
- Collaborate with frontend teams to aid in the integration of React-based user interfaces with backend APIs
- Modernize and migrate legacy systems to cloud-native architectures
- Provide guidance on architectural decisions involving data workflows, storage formats, and service patterns
- Decompose complex, cross-cutting tasks into organized delivery plans
- Mentor junior and mid-level engineers on data engineering best practices, extending from streaming to transformation layers
- Review and document architectural choices and technical designs for clarity and alignment
- Rotate across different projects (every 6-12 months) dealing with large-scale data and infrastructure challenges, frequently within banking and financial services
- Lead technical execution on greenfield builds, real-time analytics platforms, and high-throughput systems
- Serve as a hands-on engineering partner to client teams, fostering long-term technical trust and delivering significant impact
Technologies:
- AI
- API
- AWS
- Azure
- Backend
- CI/CD
- Cloud
- Databricks
- ETL
- Frontend
- Hadoop
- Java
- Kafka
- LLM
- Python
- React
- SQL
- Spark
- Spring
- microservices
- Big Data
- DevOps
- Embedded
- Support
More:
At Tactable, we are dedicated to transforming organizations through innovative software solutions. As a hybrid cloud, data, and API engineering firm, we prioritize expert delivery, strong partnerships, and unwavering commitment to quality. Our team is composed of engineers who are passionate about client collaboration and project lifecycles, working at startup speed while adhering to the stringent standards of enterprise-grade engineering. We have a strong demand from leading clients and a promising trajectory for growth. We offer a dynamic environment where developers can thrive and make a meaningful impact through their work.
last updated 40 week of 2026