Lead Software Engineer

Responsibilities

• Deliver large-scale cloud-native data platforms on AWS leveraging REST APIs, microservices, and event-driven applications for scalability and resilience.
• Work hands-on across Java, Python, Spark, TypeScript, JavaScript, Angular, AWS services, event-driven architectures, and SQL/NoSQL databases.
• Lead technical initiatives focused on performance, scalability, reliability, security, governance, and cost efficiency.
• Partner with global engineering, product management, architecture, and business stakeholders to align solutions with objectives.
• Own the end-to-end SDLC including requirements, design, development, deployment, observability, and documentation.
• Mentor junior engineers and promote a culture of innovation, accountability, collaboration, and technical excellence.

Requirements

• 8-10 years of software engineering with expertise in scalable UX-driven applications and distributed systems.
• Proven experience with REST APIs, microservices, Kubernetes, and distributed architectures.
• Experience in Data Warehousing, Data Lakes, Delta Lake, and modern big data ecosystem designs.
• Hands-on expertise in Python, Java, and Angular with knowledge of object-oriented and functional programming.
• Expertise in PySpark and Apache Spark for high-performance distributed data processing.
• Depth in microservices with Kubernetes for eventing and serving.
• Extensive AWS experience including S3, Lambda, API Gateway, and EventBridge.
• Experience with Kafka, SNS, SQS, and databases such as PostgreSQL, SQL Server, Aurora, DynamoDB, MongoDB, and Redis.
• Hands-on with Terraform and Ansible for Infrastructure as Code.
• Strong CI/CD and DevOps practices with tools such as Jenkins, GitHub/GitLab, Bitbucket, and GoCD.
• Robust testing practices including unit, integration, and regression testing.
• Strong analytical skills for diagnosing and resolving complex technical problems.
• Exposure to Generative AI, LLMs, RAG architectures, and Agentic AI systems.
• Nice to have: PySpark with Databricks, experience with Azure and/or GCP, and building privacy-safe CDPs or MarTech data platforms.

Qualifications

B.E./B.Tech/M.Tech/MCA in Computer Science, Information Technology, or related field.

Skills

• REST APIs
• Microservices
• Kubernetes
• Distributed architectures
• Data Warehousing
• Data Lakes
• Delta Lake
• PySpark
• Apache Spark
• Kafka
• SNS
• SQS
• Terraform
• Ansible
• Jenkins
• GitHub/GitLab
• Bitbucket
• GoCD
• Unit Testing
• Integration Testing
• Regression Testing
• Generative AI
• LLMs
• RAG Architectures
• Agentic AI Systems

Benefits

• Medical
• Dental
• Vision
• 401k with company matching
• Life Insurance

Pay

• $85.00 to $90.00/hr.

Schedule

• Hybrid at least 2 days per week in office in Wakefield, MA