A UI Automation Tester is responsible for designing, developing, and executing automated tests to
ensure the quality, functionality, and optimal user experience of software applications. This role is a
key part of the modern agile development lifecycle, involving collaboration with cross-functional
teams to integrate testing into continuous integration and delivery (CI/CD) pipelines.

What does your day look like at Payoda?

 4–6 years of experience in Quality Engineering / Test Automation
 Primary focus: UI/UX automation (70%); Secondary focus: Backend/API automation (30%)
 Strong focus on frontend/UI automation, especially UX validation.
 Strong coding proficiency in Python/Javascript and modern UI frameworks.

 Design and Strategy: Identify test cases suitable for automation and design comprehensive
automation test strategies and plans.

 Framework Development: Create, enhance, and maintain robust and scalable automation
frameworks (e.g., Hybrid, Data-Driven, Page Object Model) from scratch using programming
languages like Python, or JavaScript.

 Scripting and Execution: Develop, debug, and run automated test scripts using industry-standard
tools (e.g., Selenium, Playwright, Cypress) for functional, regression, smoke, and end-to-end testing.

 Defect Management: Analyze test results, identify failures, perform root-cause analysis, and log
defects with detailed documentation (steps to reproduce, screenshots, etc.) in bug-tracking systems
like Jira.

 CI/CD Integration: Integrate automated test suites into CI/CD pipelines (e.g., Jenkins, GitLab) to
enable continuous testing and faster feedback loops.

 Collaboration: Work closely with developers, product managers, business analysts, and other QA
engineers to understand requirements, refine acceptance criteria, and ensure comprehensive test
coverage.

 Documentation and Reporting: Maintain clear documentation of test cases, scripts, and results, and
provide regular status reports to stakeholders.

What do we look for in you?

Technical Proficiency:
o Programming Languages: Strong proficiency in at least one language such as Python, or
JavaScript/TypeScript.

o Automation Tools: Hands-on experience with UI automation tools like Selenium WebDriver,
Playwright, Cypress, or Appium for mobile applications.

o Testing Methodologies: Deep understanding of software testing life cycle (STLC), Agile/Scrum
methodologies, and QA principles.

o Web Technologies: Knowledge of HTML, CSS, DOM analysis, XPath, and CSS selectors.

o Other Tools: Experience with version control (Git, Bitbucket), CI/CD tools (Jenkins, GitLab), API
testing tools (Postman, REST Assured), and database testing with SQL.

Soft Skills:
o Excellent analytical and problem-solving abilities.
o Strong attention to detail and a passion for quality.
o Effective communication and collaboration skills.
o Proactive mindset and a self-starter attitude.

Role Overview We are seeking an experienced PostgreSQL DBA responsible for database performance, availability, security, backup/recovery, and production reliability. This role will be critical in designing scalable database architecture and providing round-the-clock support for production environments.

The ideal candidate is proactive, highly reliable, and comfortable working in high-availability SaaS environments. We are looking for a hands-on PostgreSQL Database Administrator to own, manage, and optimize our database systems and provide 24/7 production support coverage.

Key Responsibilities

Database Administration & Management

• Install, configure, and maintain PostgreSQL databases in production and non-production environments. • Manage database upgrades, patches, and migrations. • Design and implement high-availability (HA) and disaster recovery (DR) strategies. • Configure and maintain replication (streaming, logical, etc.).

Performance Optimization

• Monitor and tune database performance (queries, indexes, configuration tuning). • Perform root cause analysis for database-related issues. • Optimize schema design and query performance in collaboration with engineering teams.

Backup, Recovery & Reliability

• Implement and test backup and restore procedures. • Ensure point-in-time recovery (PITR) capabilities. • Regularly validate disaster recovery readiness.

Production Support (24/7)

• Respond to and resolve production incidents within defined SLAs. • Conduct post-incident analysis and implement preventive measures.

Security & Compliance

• Implement database security best practices (roles, access control, encryption). • Perform vulnerability assessments and ensure compliance with security standards. • Monitor database logs and suspicious activities.

Automation & DevOps Collaboration

• Automate routine DBA tasks using scripting (Shell, Python, etc.). • Work closely with DevOps for CI/CD integration and infrastructure improvements. • Manage cloud-based PostgreSQL deployments (AWS RDS, Azure, GCP, or self-hosted).

Required Skills & Qualifications

• 5+ years of hands-on PostgreSQL DBA experience. • Strong knowledge of PostgreSQL architecture and internals. • Experience with: o Replication, HA setups, and failover configurations o Backup and recovery tools (pg_dump, pg_basebackup, WAL archiving, PITR, etc.) o Performance tuning, query optimization, and indexing strategies • Experience managing PostgreSQL in production SaaS environments. • Strong experience running PostgreSQL in Kubernetes environments (StatefulSets, Operators like CrunchyData/CloudNativePG/Zalando, persistent volumes, scaling strategies). • Experience managing PostgreSQL on Kubernetes (K8s) including HA, upgrades, failover, and storage management. • Experience with Vector Databases or PostgreSQL-based vector extensions (e.g., pgvector) for AI/ML workloads. • Strong understanding of Linux systems administration. • Experience with monitoring tools (Zabbix, pgAdmin, Prometheus, Grafana, etc.). • Familiarity with cloud platforms (AWS/Azure/GCP). • Experience with scripting (Bash, Python, or similar).

Preferred Qualifications

• Experience designing and managing PostgreSQL clusters in Kubernetes at scale. • Hands-on experience with vector search optimization and indexing (HNSW, IVFFlat, etc.). • Experience with containerized environments (Docker/Kubernetes). • Experience with Infrastructure as Code (Terraform, Ansible). • Knowledge of database security standards and compliance frameworks. • Experience supporting high-transaction and AI-driven systems. • PostgreSQL certification is a plus.

Soft Skills

• Strong problem-solving and troubleshooting abilities. • Ability to work independently and take ownership. • Excellent communication skills. • Ability to remain calm under pressure during production incidents.

Availability Requirements

• Willingness to provide 24/7 production support coverage. • Ability to respond to critical incidents within defined response times.

This role supports machine learning data pipelines and backend data workflows. The focus is on data
engineering for ML. The engineer will work closely with Data Science and ML Engineering teams to build,
process, and serve data required for ML training and inference.

What you’ll be doing?
 Build and maintain scalable data pipelines for ML workflows
 Implement ETL / large-scale data processing using Spark (Scala or Python)
 Design and build benchmarks.
 Assist with ML pipeline operationalization (batch/stream ingestion, data readiness)
 Develop backend components for data and ML services
 Partner with ML engineers to understand data dependencies and performance needs

What’s it going to take?
 Strong hands-on experience with either Python/PySpark or Scala/Spark
 Good understanding of data engineering concepts and large-scale data processing
 Exposure to machine learning workflows and data requirements for ML models
 Experience with backend development and data-driven services
 Prompt engineering

Nice to Have
 Basic understanding of LLM/VLM training/fine-tuning.
 Prior experience with LLM or relevant data processing
 Experience with texutal and image data preprocessing
Prior experience working with GPS trace data

What you’ll be doing?
The Maps team is developing tools to analyze, visualize, process, manage and curate data on a large scale.
Our team combines disparate signals such as data analytics, community engagement, and user feedback to
improve the Maps Platform. On any given day you may be asked to analyze large data sets to identify errors
in the map, design and implement a complex algorithm for resolving the issue, review the solution with a team
of engineers and analysts, and integrate the resulting solution into the data processing pipeline.
We are looking for engineers who can be part of the team building a massive, scalable, distributed system
for enabling the maps data platform. Successful candidates will have exceptional engineering and
communication skills and believe that data-driven feedback leads to great products.

What’s it going to take?
· 3+ years of experience working in a software product development organization building modern
and scalable big data applications
· Expertise with functional programming, preferably Scala
· Experience in developing REST-based microservices, preferably with Play as MVC framework
· In-depth knowledge of developing applications using Elastic search, Kafka messaging
· Experience with NoSQL and SQL databases with familiarity with the Cassandra database
· Experience in building low latency high transactional services

Additional Requirements
Familiarity with GeoSpatial concepts is a plus

In this role you'll be responsible for building machine learning based systems and conduct data analysis that
improves the quality of our large geospatial data. You’ll be developing NLP models to extract information,
using outlier detection to identifying anomalies and applying data science methods to quantify the quality of
our data. You will take part in the development, integration, product ionisation and deployment of the models
at scale, which would require a good combination of data science and software development.

What you’ll be doing?
 Development of machine learning models
 Building and maintaining software development solutions
 Provide insights by applying data science methods
 Take ownership of delivering features and improvements on time

What’s it going to take?
 Strong programming skills and extensive experience with Python
 Professional experience working with LLMs, transformers and open-source models from Hugging Face
 Professional experience working with machine learning and data science, such as classification,
feature engineering, clustering, anomaly detection and neural networks
 Knowledgeable in classic machine learning algorithms (NLP, SVM, Random Forest, Naive Bayes, KNN
etc).
 Experience using deep learning libraries and platforms, such as PyTorch
 Experience with frameworks such as Sklearn, Numpy, Pandas, Polars
 Excellent analytical and problem solving skills
 Excellent oral and written communication skills Extra Merit Qualifications
 Knowledge in at least one of the following: NLP, information retrieval, data mining
 Ability to do statistical modeling and building predictive models
 Programming skills and experience with Scala and/or Java

What do we look for in you

4 to 8 years experienced
● Attention to detail
● Background in Linux, Unix, C/C++, Python and Golang
● Understanding of complete backend workflow for web apps
● Experience building third party software integration and API’s
● Release engineering skills (pip, rpm, deb, rvm)
● Experience with CI platforms (Jenkins)
● Familiarity with Agile software development methodology
● Creative thinker and team player
● Should be ready to adopt new technologies
● Excellent communication skills
● Resourcefulness and troubleshooting aptitude
Value Adds:
● Working experience in docker and K8s deployments
● Working Experience in AWS/GCP
● Working experience with Network technologies
Let’s celebrate work. Join us!