Data engineer

Job Title : Backend Developer (Node.js or Python/Django)

Experience : 2 to 5 Years

Location : Connaught Place, Delhi (Work From Office)

Job Summary :

We are looking for a skilled and motivated Backend Developer (Node.js or Python/Django) to join our in-house engineering team.

Key Responsibilities :

• Design, develop, test, and maintain robust backend systems using Node.js or Python/Django.
• Build and integrate RESTful APIs including third-party Authentication APIs (OAuth, JWT, etc.).
• Work with data stores like Redis and Elasticsearch to support caching and search features.
• Collaborate with frontend developers, product managers, and QA teams to deliver complete solutions.
• Ensure code quality, maintainability, and performance optimization.
• Write clean, scalable, and well-documented code.
• Participate in code reviews and contribute to team best practices.

Required Skills :

• 2 to 5 Years of hands-on experience in backend development.
• Proficiency in Node.js and/or Python (Django framework).
• Solid understanding and experience with Authentication APIs.
• Experience with Redis and Elasticsearch for caching and full-text search.
• Strong knowledge of REST API design and best practices.
• Experience working with relational and/or NoSQL databases.
• Must have completed at least 2 end-to-end backend projects.

Nice to Have :

• Experience with Docker or containerized environments.
• Familiarity with CI/CD pipelines and DevOps workflows.
• Exposure to cloud platforms like AWS, GCP, or Azure.

Job Title : Python Backend Lead / Senior Python Developer

Experience : 6 to 10 Years

Location : Bangalore (CV Raman Nagar)

Openings : 8

Interview Rounds : 1 Virtual + 1 In-Person (Face-to-Face with Client)

Note : Only local Bangalore candidates will be considered

About the Role :

We are seeking an experienced Python Backend Lead / Senior Python Developer to design, develop, and optimize scalable backend solutions.

The role involves working with large-scale data, building efficient APIs, integrating middleware solutions, and ensuring high performance and reliability.

You will lead a team of developers while also contributing hands-on to coding, design, and architecture.

Mandatory Skills : Python (Pandas, NumPy, Matplotlib, Plotly), FastAPI/FlaskAPI, SQL & NoSQL (MongoDB, CRDB, Postgres), Middleware tools (Mulesoft/BizTalk), CI/CD, RESTful APIs, OOP, OOD, DS & Algo, Design Patterns.

Key Responsibilities :

• Lead backend development projects using Python (FastAPI/FlaskAPI).
• Design, build, and maintain scalable APIs and microservices.
• Work with SQL and NoSQL databases (MongoDB, CRDB, Postgres).
• Implement and optimize middleware integrations (Mulesoft, BizTalk).
• Ensure smooth deployment using CI/CD pipelines.
• Apply Object-Oriented Programming (OOP), Design Patterns, and Data Structures & Algorithms to deliver high-quality solutions.
• Collaborate with cross-functional teams (frontend, DevOps, product) to deliver business objectives.
• Mentor and guide junior developers, ensuring adherence to best practices and coding standards.

Required Skills :

• Strong proficiency in Python with hands-on experience in Pandas, NumPy, Matplotlib, Plotly.
• Expertise in FastAPI / FlaskAPI frameworks.
• Solid knowledge of SQL & NoSQL databases (MongoDB, CRDB, Postgres).
• Experience with middleware tools such as Mulesoft or BizTalk.
• Proficiency in RESTful APIs, Web Services, and CI/CD pipelines.
• Strong understanding of OOP, OOD, Design Patterns, and DS & Algo.
• Excellent problem-solving, debugging, and optimization skills.
• Prior experience in leading teams is highly desirable.

Job Title : Senior Python Backend Developer

Experience Required : 5+ Years

Location : Gurgaon

Joining : Immediate Joiner Preferred

Employment Type : Full-Time

Job Summary :

We are looking for a highly skilled Senior Python Backend Developer with a minimum of 5 years of experience in Python and its modern web frameworks.

The ideal candidate will be responsible for developing scalable backend services, designing robust APIs, and ensuring optimal performance and security of backend systems.

Mandatory Skills : Python, Django, Flask, Streamlit, Starlette, REST API development, scalable backend services.

Key Responsibilities :

• Design, build, and maintain RESTful APIs and backend systems using Python.
• Work with frameworks such as Django, Flask, Streamlit, Starlette.
• Develop scalable and high-performance backend services.
• Collaborate with frontend developers and product teams to deliver seamless integrations.
• Write clean, maintainable, and testable code.
• Troubleshoot and resolve performance and scalability issues.
• Ensure code quality through automated testing and code reviews.

Required Skills :

• Minimum 5 years of backend development experience in Python.
• Strong expertise in Django, Flask, Streamlit, and/or Starlette.
• Proven experience with API design and development.
• Strong understanding of system architecture, data modeling, and scalability best practices.
• Familiarity with CI/CD pipelines, Docker, and cloud environments is a plus.

Nice to Have :

• Experience with async programming (e.g., using FastAPI, Starlette).
• Familiarity with PostgreSQL, MongoDB, or other relational/noSQL databases.
• Exposure to microservices architecture.

Location: Mumbai, Maharashtra, India

Sector: Technology, Information & Media

Company Size: 500 - 1,000 Employees

Employment: Full-Time, Permanent

Experience: 10 - 14 Years (Engineering Leadership)

Level: Engineering Manager / Group EM

ABOUT THIS MANDATE :

Recruiting Bond has been exclusively retained by one of India's most prominent and well-established digital platform organisations operating at the intersection of Technology, Information, and Media to identify and place an exceptional Engineering Manager who can lead engineering teams through an enterprise-wide AI adoption and digital transformation agenda.

This is a high-impact, hands-on leadership role at the nexus of people, product, and technology. The organisation is executing one of the most ambitious AI transformation programmes in its sector and this Engineering Manager will be a core driver of that change. You will lead multiple squads, own engineering delivery end-to-end, embed AI tooling and practices into the team's DNA, and shape the engineering culture of tomorrow.

We are seeking leaders who code when it matters, who build systems and teams with equal conviction, and who view AI not as a trend but as a fundamental shift in how great software is built.

THE OPPORTUNITY AT A GLANCE :

AI-First Engineering Culture :

• Own AI adoption across your squads - from LLM tooling integration to automation-first delivery workflows. Make AI a default, not an afterthought.

Hands-On Engineering Leadership :

• Stay close to the code. Lead architecture reviews, unblock engineers, and set the technical bar - not just the management agenda.

People & Org Builder :

• Grow engineers into leaders. Build squads of 615 across functions. Drive hiring, career frameworks, and a culture of psychological safety.

KEY RESPONSIBILITIES :

1. Hands-On Technical Engagement :

• Remain deeply embedded in the technical work participate in design reviews, architecture decisions, and critical code reviews
• Set and uphold the engineering quality bar : performance benchmarks, security standards, test coverage, and release quality
• Provide technical direction on backend platform strategy, API design, service decomposition, and data architecture
• Identify and resolve systemic technical debt and architectural risks across team-owned services
• Unblock engineers by diving into complex problems debugging, pair programming, and system analysis when it matters
• Own key technical decisions in collaboration with Tech Leads and Principal Engineers; balance pragmatism with long-term sustainability

2. AI Adoption, Integration & Transformation (2026 Mandate) :

• Define and execute the team's AI adoption roadmap - from developer tooling to product-facing AI features
• Champion the integration of GenAI tools (GitHub Copilot, Cursor, Claude, ChatGPT) across the full engineering workflow coding, testing, documentation, incident response
• Embed LLM-powered capabilities into the product : recommendation engines, intelligent search, conversational interfaces, content generation, and predictive systems
• Lead evaluation and adoption of AI-assisted SDLC practices : automated code review, AI-generated test suites, intelligent observability, and anomaly detection
• Partner with Data Science and ML Platform teams to productionise ML models with robust MLOps pipelines
• Build team literacy in prompt engineering, RAG (Retrieval-Augmented Generation), and AI agent frameworks
• Create an experimentation culture : run structured AI pilots, measure productivity impact, and scale what works
• Stay ahead of the AI tooling landscape and advise senior leadership on strategic AI investments and engineering implications

3. People Leadership & Team Development :

• Lead, manage, and grow squads of 6 - 15 engineers across seniority levels (L2 through L6 / Junior through Staff)
• Conduct structured 1 : 1s, career growth conversations, and development planning with every direct report
• Design and execute personalised AI upskilling programmes ensure every engineer develops practical AI fluency by end of 2026
• Build and maintain a high-performance team culture : clarity of ownership, accountability, fast feedback loops, and psychological safety
• Drive performance management fairly and rigorously recognise top performers, manage underperformance constructively
• Lead technical hiring end-to-end : define job requirements, conduct bar-raising interviews, and make data-driven hire decisions
• Contribute to engineering career frameworks and level definitions in partnership with the VP / Director of Engineering

4. Engineering Delivery & Execution Excellence :

• Own end-to-end delivery for multiple product squads from planning and scoping through production release and post-launch stability
• Implement and refine agile delivery frameworks (Scrum, Kanban, Shape Up) calibrated to squad needs and product cadence
• Drive predictable delivery : maintain healthy sprint velocity, manage WIP limits, and ensure dependency resolution across teams.
• Establish and own engineering KPIs : DORA metrics (deployment frequency, lead time, MTTR, change failure rate), uptime SLOs, and velocity trends
• Lead incident management : build blameless post-mortem culture, own RCA processes, and drive systemic reliability improvements
• Balance technical debt repayment with feature velocity negotiate prioritisation transparently with Product leadership

5. Strategic Leadership & Cross-Functional Influence :

• Serve as the primary engineering partner for Product, Design, Data, and Business stakeholders translate ambiguity into executable engineering plans
• Participate in quarterly roadmap planning, capacity forecasting, and OKR definition for engineering teams
• Represent engineering in leadership forums articulate technical constraints, risks, and opportunities in business terms
• Contribute to org-wide engineering strategy : platform investments, build-vs-buy decisions, and shared infrastructure priorities
• Build relationships across geographies (Mumbai HQ + distributed teams) to maintain alignment and delivery cohesion
• Act as a culture carrier and ambassador for engineering excellence, innovation, and responsible AI use

AI TRANSFORMATION LEADERSHIP 2026 EXPECTATIONS :

In 2026, Engineering Managers at this organisation are expected to be active architects of AI transformation not passive observers. The following outlines the specific AI leadership expectations for this role :

AI Developer Productivity

• Drive measurable uplift in developer velocity through AI tooling adoption. Target : 30%+ reduction in code review cycle time and 40%+ increase in test coverage automation by Q3 2026.

LLM & GenAI Product Features

• Own delivery of GenAI-powered product capabilities : intelligent content, semantic search, personalisation, and conversational UX in production, at scale.

AI-Augmented Observability

• Implement AI-driven monitoring and anomaly detection pipelines. Reduce MTTR by leveraging predictive alerting, intelligent runbooks, and auto-remediation scripts.

Team AI Fluency :

• Build mandatory AI literacy across all engineering levels.
• Every engineer understands prompt engineering basics, AI ethics guardrails, and responsible AI deployment practices.

Responsible AI Governance :

• Partner with Security, Legal, and Data Privacy to ensure all AI deployments meet compliance standards, bias mitigation requirements, and explainability benchmarks.

TECHNOLOGY STACK & DOMAIN FAMILIARITY REQUIRED :

• Languages: Java/ Go/ Python/ Node.js /PHP /Rust (must be hands-on in at least 2)
• Cloud: AWS / GCP / Azure (multi-cloud exposure strongly preferred)
• AI & GenAI: OpenAI / Anthropic / Gemini APIs /LangChain /LlamaIndex / RAG / Vector DBs / GitHub
• Copilot: Cursor /Hugging Face
• Containers: Docker /Kubernetes /Helm /Service Mesh (Istio / Linkerd)
• Databases: PostgreSQL /MongoDB / Redis / Cassandra / Elasticsearch / Pinecone (Vector DB)
• Messaging: Apache Kafka /RabbitMQ /AWS SQS/SNS /Google Pub/Sub
• MLOps & DataOps: MLflow /Kubeflow / SageMaker / Vertex AI /Airflow /dbt
• Observability: Datadog /Prometheus /Grafana /OpenTelemetry / Jaeger /ELK Stack
• CI/CD & IaC: GitHub Actions ArgoCD / Jenkins / Terraform /Ansible /Backstage (IDP)

QUALIFICATIONS & CANDIDATE PROFILE :

Education :

• B.E. / B.Tech or M.E. / M.Tech from a Tier-I or Tier-II Institution - CS, IS, ECE, AI/ML streams strongly preferred
• Demonstrated engineering depth and leadership impact may complement institution pedigree

Experience :

• 10 to 14 years of progressive engineering experience, with at least 3 years in a formal Engineering Manager or equivalent people-leadership role
• Proven track record of managing and scaling engineering teams (615+ engineers) in a fast-growing SaaS or digital product environment
• Hands-on backend engineering background must be able to read, write, and critique production code
• Direct experience driving AI/ML feature delivery or AI tooling adoption within engineering organisations
• Exposure across start-up, mid-size, and large-scale product organisations, preferred adaptability is a core requirement
• Strong CS fundamentals: distributed systems, algorithms, system design, and software architecture
• Demonstrated career stability minimum of 2 years of average tenure per organisation.

The Ideal Engineering Manager in 2026 :

• Leads with context, not control, empowers engineers while maintaining accountability and quality
• Is fluent in both people language and technical language, switches registers naturally with engineers and executives alike
• Sees AI as a force multiplier for the team, not a threat. Actively experiments with and advocates for AI tooling
• Measures success by team outcomes, not personal output. Takes pride in what the team ships, not what they build alone
• Creates feedback loops obsessively between product and engineering, between seniors and juniors, between metrics and decisions
• Has strong opinions, loosely held, brings conviction to discussions but updates on evidence
• Invests in engineering excellence as seriously as delivery velocity knows that quality and speed are not opposites

WHY THIS ROLE STANDS APART :

AI Transformation at Scale :

• Lead one of the most significant AI adoption programmes in India's digital media sector.
• Our decisions will shape how hundreds of engineers work in 2026 and beyond.

Hands-On & Strategic Balance :

• A rare EM role that actively encourages technical depth.
• Stay close to the code while owning the people agenda - the best of both worlds.

Established Platform, Real Scale :

• 5001,000 engineers, proven product-market fit, and the org maturity to execute.
• This is not a greenfield startup gamble it is a serious company with serious ambition.

Clear Leadership Growth Path :

• A visible, direct path toward Director / VP of Engineering.
• Senior leadership is invested in growing its next generation of technology executives.

🚀 Hiring: Data Engineer ( Azure ) at Deqode

⭐ Experience: 5+ Years

📍 Location: Pune, Bhopal, Jaipur, Gurgaon, Delhi, Banglore,

⭐ Work Mode:- Hybrid

⏱️ Notice Period: Immediate Joiners

(Only immediate joiners & candidates serving notice period)

⭐ Hiring: Databricks Data Engineer – Lakeflow | Streaming | DBSQL | Data Intelligence

We are looking for a Databricks Data Engineer ( Azure ) to build reliable, scalable, and governed data pipelines powering analytics, operational reporting, and the Data Intelligence Layer.

🔹 Key Responsibilities

✅ Build optimized batch pipelines using Delta Lake (partitioning, OPTIMIZE, Z-ORDER, VACUUM)

✅ Implement incremental ingestion using Databricks Autoloader with schema evolution & checkpointing

✅ Develop Structured Streaming pipelines with watermarking, late data handling & restart safety

✅ Implement declarative pipelines using Lakeflow

✅ Design idempotent, replayable pipelines with safe backfills

✅ Optimize Spark workloads (AQE, skew handling, shuffle & join tuning)

✅ Build curated datasets for Databricks SQL (DBSQL), dashboards & downstream applications

✅ Package and deploy using Databricks Repos & Asset Bundles (CI/CD)

Ensure governance using Unity Catalog and embedded data quality checks

✅ Mandatory Skills (Must Have)

👉 Databricks & Delta Lake (Advanced Optimization & Performance Tuning)

👉 Structured Streaming & Autoloader Implementation

👉 Databricks SQL (DBSQL) & Data Modeling for Analytics

What We’re Looking For

• 4+ years of backend development experience in scalable web applications.
• Strong expertise in Python, Django ORM, and RESTful API design.
• Familiarity with relational databases like PostgreSQL and MySQL databases
• Comfortable working in a startup environment with multiple priorities.
• Understanding of cloud-native architectures and SaaS models.
• Strong ownership mindset and ability to work with minimal supervision.
• Excellent communication and teamwork skills.

Role Overview:

The AI Research Intern will focus on natural language processing (NLP) and working with large language models (LLMs). They will assist in refining and testing the retrieval-augmented generation (RAG) system for CopilotGTM.

Key Responsibilities:

• Assist in developing and refining NLP models to answer customer queries.
• Research and implement improvements to minimize hallucinations in the LLM.
• Test RAG model configurations and provide feedback to improve accuracy.
• Work with the engineering team to improve real-time product recommendations and responses.
• Analyze datasets and fine-tune models for specific use cases (e.g., sales, compliance).

Skills Required:

• Strong understanding of NLP and familiarity with LLMs (GPT, BERT, etc.).
• Basic coding experience in Python.
• Knowledge of data handling, data processing, and model training.
• Problem-solving ability and eagerness to experiment with new techniques.

Preferred:

• Experience with libraries like Hugging Face, PyTorch, or TensorFlow.
• Familiarity with retrieval-augmented generation (RAG) systems.

• Work with stakeholders and fellow developers.
• Design and implement Python code using the Django framework.
• Identify and fix bottlenecks that may arise from inefficient code.
• Identify and fix software bugs.
• Create a wide variety of unit tests to verify the functionality of software.
• Manage the security of the platform.
• Write detailed documentation around the code.
• Knowledge of front end languages.