Senior Data Engineering Role - Google Cloud Platform with Spark

• Creating and managing ETL/ELT pipelines based on requirements
• Build PowerBI dashboards and manage datasets needed.
• Work with stakeholders to identify data structures needed for future and perform any transformations including aggregations.
• Build data cubes for real-time visualisation needs and CXO dashboards.

Required Tech Skills

• Microsoft PowerBI & DAX
• Python, Pandas, PyArrow, Jupyter Noteboks, ApacheSpark
• Azure Synapse, Azure DataBricks, Azure HDInsight, Azure Data Factory

1. Data Engineer

 Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON

Mandatory Requirements  

• Experience in AWS Glue
• Experience in Apache Parquet 
• Proficient in AWS S3 and data lake 
• Knowledge of Snowflake
• Understanding of file-based ingestion best practices.
• Scripting language - Python & pyspark 

CORE RESPONSIBILITIES 

• Create and manage cloud resources in AWS 
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 
• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
• Define process improvement opportunities to optimize data collection, insights and displays.
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 
• Identify and interpret trends and patterns from complex data sets 
• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 
• Key participant in regular Scrum ceremonies with the agile teams  
• Proficient at developing queries, writing reports and presenting findings 
• Mentor junior members and bring best industry practices 

 QUALIFICATIONS 

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 
• Strong background in math, statistics, computer science, data science or related discipline
• Advanced knowledge one of language: Java, Scala, Python, C# 
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  
• Proficient with
• Data mining/programming tools (e.g. SAS, SQL, R, Python)
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
• Data visualization (e.g. Tableau, Looker, MicroStrategy)
• Comfortable learning about and deploying new technologies and tools. 
• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 
• Good written and oral communication skills and ability to present results to non-technical audiences 
• Knowledge of business intelligence and analytical tools, technologies and techniques.

Familiarity and experience in the following is a plus:  

• AWS certification
• Spark Streaming 
• Kafka Streaming / Kafka Connect 
• ELK Stack 
• Cassandra / MongoDB 
• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

Skills and requirements

• Experience analyzing complex and varied data in a commercial or academic setting.
• Desire to solve new and complex problems every day.
• Excellent ability to communicate scientific results to both technical and non-technical team members.

Desirable

• A degree in a numerically focused discipline such as, Maths, Physics, Chemistry, Engineering or Biological Sciences..
• Hands on experience on Python, Pyspark, SQL
• Hands on experience on building End to End Data Pipelines.
• Hands on Experience on Azure Data Factory, Azure Data Bricks, Data Lake - added advantage
• Hands on Experience in building data pipelines.
• Experience with Bigdata Tools, Hadoop, Hive, Sqoop, Spark, SparkSQL
• Experience with SQL or NoSQL databases for the purposes of data retrieval and management.
• Experience in data warehousing and business intelligence tools, techniques and technology, as well as experience in diving deep on data analysis or technical issues to come up with effective solutions.
• BS degree in math, statistics, computer science or equivalent technical field.
• Experience in data mining structured and unstructured data (SQL, ETL, data warehouse, Machine Learning etc.) in a business environment with large-scale, complex data sets.
• Proven ability to look at solutions in unconventional ways. Sees opportunities to innovate and can lead the way.
• Willing to learn and work on Data Science, ML, AI.

• 5+ years of experience building real-time and distributed system architecture, from whiteboard to production
• Strong programming skills in Python, Scala  and SQL.
• Versatility. Experience across the entire spectrum of data engineering, including:
• Data stores (e.g., AWS RDS, AWS Athena, AWS Aurora, AWS Redshift)
• Data pipeline and workflow orchestration tools (e.g., Azkaban, Airflow)
• Data processing technologies (e.g., Spark, Pentaho)
• Deployment and monitoring large database clusters in public cloud platforms (e.g., Docker, Terraform, Datadog)
• Creating ETL or ELT pipelines that transform and process petabytes of structured and unstructured data in real-time
• Industry experience building and productionizing innovative end-to-end Machine Learning systems is a plus.

Role: Data Engineer  
Company: PayU

Location: Bangalore/ Mumbai

Experience : 2-5 yrs

About Company:

PayU is the payments and fintech business of Prosus, a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities.

The leading online payment service provider in 36 countries, PayU is dedicated to creating a fast, simple and efficient payment process for merchants and buyers. Focused on empowering people through financial services and creating a world without financial borders where everyone can prosper, PayU is one of the biggest investors in the fintech space globally, with investments totalling $700 million- to date. PayU also specializes in credit products and services for emerging markets across the globe. We are dedicated to removing risks to merchants, allowing consumers to use credit in ways that suit them and enabling a greater number of global citizens to access credit services.

Our local operations in Asia, Central and Eastern Europe, Latin America, the Middle East, Africa and South East Asia enable us to combine the expertise of high growth companies with our own unique local knowledge and technology to ensure that our customers have access to the best financial services.

India is the biggest market for PayU globally and the company has already invested $400 million in this region in last 4 years. PayU in its next phase of growth is developing a full regional fintech ecosystem providing multiple digital financial services in one integrated experience. We are going to do this through 3 mechanisms: build, co-build/partner; select strategic investments. 

PayU supports over 350,000+ merchants and millions of consumers making payments online with over 250 payment methods and 1,800+ payment specialists. The markets in which PayU operates represent a potential consumer base of nearly 2.3 billion people and a huge growth potential for merchants. 

Job responsibilities:

• Design infrastructure for data, especially for but not limited to consumption in machine learning applications 
• Define database architecture needed to combine and link data, and ensure integrity across different sources 
• Ensure performance of data systems for machine learning to customer-facing web and mobile applications using cutting-edge open source frameworks, to highly available RESTful services, to back-end Java based systems 
• Work with large, fast, complex data sets to solve difficult, non-routine analysis problems, applying advanced data handling techniques if needed 
• Build data pipelines, includes implementing, testing, and maintaining infrastructural components related to the data engineering stack.
• Work closely with Data Engineers, ML Engineers and SREs to gather data engineering requirements to prototype, develop, validate and deploy data science and machine learning solutions

Requirements to be successful in this role: 

• Strong knowledge and experience in Python, Pandas, Data wrangling, ETL processes, statistics, data visualisation, Data Modelling and Informatica.
• Strong experience with scalable compute solutions such as in Kafka, Snowflake
• Strong experience with workflow management libraries and tools such as Airflow, AWS Step Functions etc. 
• Strong experience with data engineering practices (i.e. data ingestion pipelines and ETL) 
• A good understanding of machine learning methods, algorithms, pipelines, testing practices and frameworks 
• Preferred) MEng/MSc/PhD degree in computer science, engineering, mathematics, physics, or equivalent (preference: DS/ AI) 
• Experience with designing and implementing tools that support sharing of data, code, practices across organizations at scale 

Recko Inc. is looking for data engineers to join our kick-ass engineering team. We are looking for smart, dynamic individuals to connect all the pieces of the data ecosystem.

What are we looking for:

1. 3+  years of development experience in at least one of MySQL, Oracle, PostgreSQL or MSSQL and experience in working with Big Data technologies like Big Data frameworks/platforms/data stores like Hadoop, HDFS, Spark, Oozie, Hue, EMR, Scala, Hive, Glue, Kerberos etc.

2. Strong experience setting up data warehouses, data modeling, data wrangling and dataflow architecture on the cloud

3. 2+ experience with public cloud services such as AWS, Azure, or GCP and languages like Java/ Python etc

4. 2+ years of development experience in Amazon Redshift, Google Bigquery or Azure data warehouse platforms preferred

5. Knowledge of statistical analysis tools like R, SAS etc 

6. Familiarity with any data visualization software

7. A growth mindset and passionate about building things from the ground up and most importantly, you should be fun to work with

As a data engineer at Recko, you will:

1. Create and maintain optimal data pipeline architecture,

2. Assemble large, complex data sets that meet functional / non-functional business requirements.

3. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

4. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

5. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

6. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

7. Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

8. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

9. Work with data and analytics experts to strive for greater functionality in our data systems.

About Recko: 

Recko was founded in 2017 to organise the world’s transactional information and provide intelligent applications to finance and product teams to make sense of the vast amount of data available. With the proliferation of digital transactions over the past two decades, Enterprises, Banks and Financial institutions are finding it difficult to keep a track on the money flowing across their systems. With the Recko Platform, businesses can build, integrate and adapt innovative and complex financial use cases within the organization and  across external payment ecosystems with agility, confidence and at scale.  . Today, customer-obsessed brands such as Deliveroo, Meesho, Grofers, Dunzo, Acommerce, etc use Recko so their finance teams can optimize resources with automation and prioritize growth over repetitive and time-consuming tasks around day-to-day operations. 

Recko is a Series A funded startup, backed by marquee investors like Vertex Ventures, Prime Venture Partners and Locus Ventures. Traditionally enterprise software is always built around functionality. We believe software is an extension of one’s capability, and it should be delightful and fun to use.

Working at Recko: 

We believe that great companies are built by amazing people. At Recko, We are a group of young Engineers, Product Managers, Analysts and Business folks who are on a mission to bring consumer tech DNA to enterprise fintech applications. The current team at Recko is 60+ members strong with stellar experience across fintech, e-commerce, digital domains at companies like Flipkart, PhonePe, Ola Money, Belong, Razorpay, Grofers, Jio, Oracle etc. We are growing aggressively across verticals.

We are looking for BE/BTech graduates (2018/2019 pass out) who want to build their career as Data Engineer covering technologies like Hadoop, NoSQL, RDBMS, Spark, Kafka, Hive, ETL, MDM & Data Quality. You should be willing to learn, explore, experiment, develop POCs/Solutions using these technologies with guidance and support from highly experienced Industry Leaders. You should be passionate about your work and willing to go extra mile to achieve results.

We are looking for candidates who believe in commitment and in building strong relationships. We need people who are passionate about solving problems through software and are flexible.

Required Experience, Skills and Qualifications

Passionate to learn and explore new technologies

Any RDBMS experience (SQL Server/Oracle/MySQL)

Any ETL tool experience (Informatica/Talend/Kettle/SSIS)

Understanding of Big Data technologies

Good Communication Skills

Excellent Mathematical / Logical / Reasoning Skills