Python Developer, Data Engineer, Devops

Job responsibilities

- You will partner with teammates to create complex data processing pipelines in order to solve our clients' most complex challenges

- You will pair to write clean and iterative code based on TDD

- Leverage various continuous delivery practices to deploy, support and operate data pipelines

- Advise and educate clients on how to use different distributed storage and computing technologies from the plethora of options available

- Develop and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions

- Create data models and speak to the tradeoffs of different modeling approaches

- Seamlessly incorporate data quality into your day-to-day work as well as into the delivery process

- Encouraging open communication and advocating for shared outcomes

Technical skills

- You have a good understanding of data modelling and experience with data engineering tools and platforms such as Spark (Scala) and Hadoop

- You have built large-scale data pipelines and data-centric applications using any of the distributed storage platforms such as HDFS, S3, NoSQL databases (Hbase, Cassandra, etc.) and any of the distributed processing platforms like Hadoop, Spark, Hive, Oozie, and Airflow in a production setting

- Hands on experience in MapR, Cloudera, Hortonworks and/or cloud (AWS EMR, Azure HDInsights, Qubole etc.) based Hadoop distributions

- You are comfortable taking data-driven approaches and applying data security strategy to solve business problems

- Working with data excites you: you can build and operate data pipelines, and maintain data storage, all within distributed systems

- You're genuinely excited about data infrastructure and operations with a familiarity working in cloud environments

Professional skills

- You're resilient and flexible in ambiguous situations and enjoy solving problems from technical and business perspectives

- An interest in coaching, sharing your experience and knowledge with teammates

- You enjoy influencing others and always advocate for technical excellence while being open to change when needed

- Presence in the external tech community: you willingly share your expertise with others via speaking engagements, contributions to open source, blogs and more

• Play a critical role as a member of the leadership team in shaping and supporting our overall company vision, day-to-day operations, and culture.
• Set the technical vision and build the technical product roadmap from launch to scale; including defining long-term goals and strategies
• Define best practices around coding methodologies, software development, and quality assurance
• Define innovative technical requirements and systems while balancing time, feasibility, cost and customer experience
• Build and support production products
• Ensure our internal processes and services comply with privacy and security regulations
• Establish a high performing, inclusive engineering culture focused on innovation, execution, growth and development
• Set a high bar for our overall engineering practices in support of our mission and goals
• Develop goals, roadmaps and delivery dates to help us scale quickly and sustainably
• Collaborate closely with Product, Business, Marketing and Data Science
• Experience with financial and transactional systems
• Experience engineering for large volumes of data at scale
• Experience with financial audit and compliance is a plus
• Experience building a successful consumer facing web and mobile apps at scale

• Analyze and organize raw data 
• Build data systems and pipelines
• Evaluate business needs and objectives
• Interpret trends and patterns
• Conduct complex data analysis and report on results 
• Build algorithms and prototypes
• Combine raw information from different sources
• Explore ways to enhance data quality and reliability
• Identify opportunities for data acquisition
• Should have experience in Python, Django Micro Service Senior developer with Financial Services/Investment Banking background.
• Develop analytical tools and programs
• Collaborate with data scientists and architects on several projects
• Should have 5+ years of experience as a data engineer or in a similar role
• Technical expertise with data models, data mining, and segmentation techniques
• Should have experience programming languages such as Python
• Hands-on experience with SQL database design
• Great numerical and analytical skills
• Degree in Computer Science, IT, or similar field; a Master’s is a plus
• Data engineering certification (e.g. IBM Certified Data Engineer) is a plus

About Kapiva:

Kapiva is a modern ayurvedic nutrition brand focused on bringing selectively sourced, natural foods to Indian consumers. Inculcating the wisdom of India's ancient food traditions, Kapiva's high-quality product range includes herbal juices, nutrition powders, ayurvedic gummies, healthy staples, and much more. Our products are top performers on online marketplaces such as Amazon, Flipkart, Big Basket and we're growing our presence offline in a big way (Nature’s Basket, Reliance Retail, Noble Plus, etc). We’re also funded by India’s best Consumer VC Fund – Fireside Ventures.

About the role:

We are looking for a motivated data analyst with sound experience in handling web/ digital analytics, to join us as part of the Kapiva D2C Business Team. This team is primarily responsible for driving sales and customer engagement on our website (www.kapiva.in). This channel has grown 5x in revenue over the last 12 months and is poised to grow another 5x over the next six. It represents a high-growth, important part of Kapiva’s overall e-commerce growth strategy.

The mandate here is to run an end-to-end sustainable e-commerce business, boost sales through marketing campaigns, and build a cutting edge product (website) that optimizes the customer’s journey as well as increases customer lifetime value.

The Data Analyst will support the business heads by providing data-backed insights in order to drive customer growth, retention and engagement. They will be required to set-up and manage reports, test various hypotheses and coordinate with various stakeholders on a day-to-day basis.

Location: Bangalore

Job Responsibilities:

Strategy and planning:

• Work with the D2C functional leads and support analytics planning on a quarterly/ annual basis
• Identify reports and analytics needed to be conducted on a daily/ weekly/ monthly frequency
• Drive planning for hypothesis-led testing of key metrics across the customer funnel

Analytics:

• Interpret data, analyze results using statistical techniques and provide ongoing reports
• Analyze large amounts of information to discover trends and patterns
• Work with business teams to prioritize business and information needs
• Collaborate with engineering and product development teams to setup data infrastructure as needed

Reporting and communication:

• Prepare reports / presentations to present actionable insights that can drive business objectives
• Setup live dashboards reporting key cross-functional metrics
• Coordinate with various stakeholders to collect useful and required data
• Present findings to business stakeholders to drive action across the organization
• Propose solutions and strategies to business challenges

Requirements sought:

Must-haves:

• Bachelor’s/ Masters in Mathematics, Economics, Computer Science, Information Management, Statistics or related field
• 0-2 years’ experience in an analytics role, preferably consumer business. Proven experience as a Data Analyst/ Data Scientist
• High proficiency in MS Excel and SQL
• Knowledge of one or more programming languages like Python/ R. Adept at queries, report writing and presenting findings
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy - working knowledge of statistics and statistical methods
• Ability to work in a highly dynamic environment across cross-functional teams; good at coordinating with different departments and managing timelines
• Exceptional English written/verbal communication
• A penchant for understanding consumer traits and behavior and a keen eye to detail

Good to have:

• Hands-on experience with one or more web analytics tools like Google Analytics, Mixpanel, Kissmetrics, Heap, Adobe Analytics, etc.
• Experience in using business intelligence tools like Metabase, Tableau, Power BI is a plus
• Experience in developing predictive models and machine learning algorithms

• 6+ months of proven experience as a Data Scientist or Data Analyst
• Understanding of machine-learning and operations research
• Extensive knowledge of R, SQL and Excel
• Analytical mind and business acumen
• Strong Statistical understanding
• Problem-solving aptitude
• BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred

•  Strong problem-solving skills with an emphasis on product development.

Required skill

• Around 6- 8.5 years of experience and around 4+ years in AI / Machine learning space
• Extensive experience in designing large scale machine learning solution for the ML use case,  large scale deployments and establishing continues automated improvement / retraining framework.
• Strong experience in Python and Java is required.
• Hands on experience on Scikit-learn, Pandas, NLTK
• Experience in Handling of Timeseries data and associated techniques like Prophet, LSTM
• Experience in Regression, Clustering, classification algorithms
• Extensive experience in buildings traditional Machine Learning SVM, XGBoost, Decision tree and Deep Neural Network models like RNN, Feedforward is required.
• Experience in AutoML like TPOT or other
• Must have strong hands on experience in Deep learning frameworks like Keras, TensorFlow or PyTorch 
• Knowledge of Capsule Network or reinforcement learning, SageMaker is a desirable skill
• Understanding of Financial domain is desirable skill

 Responsibilities 

• Design and implementation of solutions for ML Use cases
• Productionize System and Maintain those
• Lead and implement data acquisition process for ML work
• Learn new methods and model quickly and utilize those in solving use cases