C/C++ Developer

About the Role

We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.

Key Responsibilities

• Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
• Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
• Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
• Design, develop, and maintain Apache Airflow DAGs for orchestrating reliable, scalable, and observable data pipelines.
• Design and implement data quality, observability, and governance frameworks, including automated testing, monitoring, lineage, access control, and data privacy standards.
• Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.

Required Skills

• Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
• Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
• Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
• Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
• Hands-on experience with Delta Lake, including transactional data processing, schema management, incremental data processing, and reliable batch and streaming data pipelines.
• Hands-on experience in developing dbt projects using layered architecture, incremental models, snapshots, macros/Jinja, testing, documentation, and deployment best practices.
• Expertise in advanced SQL and data modelling — dimensional modeling, slowly changing dimensions, schema evolution, and query optimization.
• Hands-on experience in developing and managing Apache Airflow DAGs, scheduling workflows, dependency management, retries, backfills, and operational monitoring.
• Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
• Strong problem-solving skills and the ability to work independently with business and analytics stakeholders.

Nice to Have

• Hands-on exposure to Microsoft Fabric for data integration and analytics.
• Experience using AI coding assistants (e.g. Claude Code, GitHub Copilot) as part of a development workflow.
• Familiarity with modern DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker/Kubernetes).
• Domain expertise in financial services.

Key Responsibilities

• Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration).

• Work on applied NLP/LLM systems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines.

• Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems.

• Own model performance, reliability, and cost — from experimentation through production deployment.

• Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration.

• Ensure systems meet the compliance, auditability, and security standards required in regulated financial environments.

What We're Looking For

• 5+ years of experience building and deploying machine learning or AI systems in production.

• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent).

• Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued.

• Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning).

• Prior experience at a strong product company, high-growth startup, or a top-tier engineering background

• Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity.

Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory

• 5+ years of experience
• FlaskAPI, RestAPI development experience
• Proficiency in Python programming.
• Basic knowledge of front-end development.
• Basic knowledge of Data manipulation and analysis libraries
• Code versioning and collaboration. (Git)
• Knowledge for Libraries for extracting data from websites.
• Knowledge of SQL and NoSQL databases
• Familiarity with RESTful APIs
• Familiarity with Cloud (Azure /AWS) technologies

Roles and Responsibilities

Excellent team player, ability to work in a global team and follow through on deadlines and Built MVC based Web Application Using JSP/Spring framework and Good knowledge of Application Servers like Tomcat and Web logic.

Good knowledge of database software like MySQL and solid understanding of DB conceptsWeb application development (including GUI design)Knowledge of web server software like - Apache Working knowledge of build and source code control tools like GitExperience with system integration testing and unit testingExcellent time management and multitasking skills Develop and implement new software programs

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• To oversee sales operation with several counties in a particular geographical location.
• Reaching the target and goal set of your area.
• Establishing, maintaining and expanding your customer base.
• Establishing, maintaining and expanding your customer base
• Servicing the needs of your existing customers
• Increasing business opportunities through various routes to market.