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Senior Python Backend Developer (Immediate Joiners Only)

MishiPay

  • Bengaluru, India
  • Competitive Package
  • 5+ Years
  • Posted Today
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About the role

Senior Python Backend Developer (Immediate Joiners Only)

MishiPay

Bangalore

Salary plus 20% bonus

Unlimited Holidays

About MishiPay

MishiPay is a global leader in next-generation checkout technology, enabling seamless in-store purchases via shoppers’ own smartphones or our minimalist, low capex kiosks.

We provide a complete checkout ecosystem - spanning self-checkout, Mobile POS, Click & Collect and traditional tills - allowing retailers to run their entire store checkout operation on MishiPay.

Our technology reduces operating costs, increases basket size and visit frequency, lowers abandonment, and unlocks rich, real-time customer data, delivering both immediate commercial impact and deeper insight into the in-store customer journey. We now have major international retail customers in the UK, Europe, Middle East, Australia and the USA, and we’re expanding!

About The Role

We are looking for Senior Python Backend Developers to join our talented engineering squad. The team is responsible for our main infrastructure and delivering the necessary tools to create the best in-store experience possible. You MUST have atleast 6 years of experience in Python, Django, and within a scaling product business, as you will need to work at speed.

You’ll work closely with the Director of Backend and other squad members, alongside the Product, Payment, Security and Delivery teams achieving the roadmap which has been set against our top business priorities. You’ll work on getting rid of tech debt, deploy best in class systems and architecture and ensure that we can scale to 1000s of stores while maintaining system performance at over 99.9% at the push of a button.

You should have experience building microservices from scratch that have over time scaled to millions of requests, experience working with retail systems such as inventory, promotions, ERP, EPOS, loyalty programmes or payments in a physical or online retail environment is a huge plus for this position. If you're a startup enthusiast who is passionate about solving complex problems and wants to learn something new everyday, we'd absolutely love to speak to you!

Key Responsibilities

  • Deliver stability of over 99.95% across MishiPay’s key platforms
  • Achieve ability to scale the infrastructure so it can handle up to 100k transactions a day
  • Design, code, and develop new features/fix bugs/add enhancements improve performance of large scale services.
  • Actively work to clear tech-debt as we continue developing new technology.
  • Coach and mentor junior team members
  • Prepare high quality technical documentation

Required Experience

  • We are looking for immediate joiners only.
  • Experience with at least one relational like PostgreSQL, MySQL & also one NoSQL database like MongoDB, Cassandra, DynamoDB
  • Hands on experience with at least one major cloud provider like AWS, Azure or GCP (Azure preferred)
  • Hands-on experience with at least one of the deployments-orchestration technologies like Kubernetes, Docker Swarm etc
  • (bonus) Hands-on experience with event-driven services and technologies like Kafka, Amazon SQS, Apache Spark etc
  • (bonus) Worked in a startup that has seen scale or coming from an entrepreneur background
  • (bonus) Experience of fintech, retail-system and technologies

Why MishiPay?

You’ll work with an inspirational multi-cultural team, based in our Dubai HQ, the US, London and Bangalore, who are redefining the retail industry globally. We offer a tight-knit, collaborative and exciting work environment, coupled with the opportunity to see the apps we develop live in action within some of the world’s largest retailers, impacting the lives of millions of shoppers.

We also offer

  • Bonuses
  • Unlimited holidays
  • Hybrid Working (36 days WFH a year)
  • Monthly Employee Awards
  • A small monthly training budget
  • Company events
  • Free lunch in Bangalore
  • MacBook
  • Career progression and a chance to work with some of the brightest minds in tech

Eligibility & process

Who can apply

Seniority: Mid-Senior level. Employment type: Full-time

Skills & stack

Python Next.js Django Microservices PostgreSQL MySQL MongoDB DynamoDB

Selection process

Details are shared by the recruiter after shortlisting.

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Python, Next.js, Django, Microservices, PostgreSQL, MySQL, MongoDB, DynamoDB) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion MishiPay Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join MishiPay as a Senior Python Backend Developer (Immediate Joiners Only)?
Highlight MishiPay's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
MishiPay Competitive Package
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