Big Data Python Developer

• Core Java: advanced level competency, should have worked on projects with core Java development.

 

• Linux shell : advanced level competency, work experience with Linux shell scripting, knowledge and experience to use important shell commands

 

• Rdbms, SQL: advanced level competency, Should have expertise in SQL query language syntax, should be well versed with aggregations, joins of SQL query language.

 

• Data structures and problem solving: should have ability to use appropriate data structure.

 

• AWS cloud : Good to have experience with aws serverless toolset along with aws infra

 

• Data Engineering ecosystem : Good to have experience and knowledge of data engineering, ETL, data warehouse (any toolset)

 

• Hadoop, HDFS, YARN : Should have introduction to internal working of these toolsets

 

• HIVE, MapReduce, Spark: Good to have experience developing transformations using hive queries, MapReduce job implementation and Spark Job Implementation. Spark implementation in Scala will be plus point.

 

• Airflow, Oozie, Sqoop, Zookeeper, Kafka: Good to have knowledge about purpose and working of these technology toolsets. Working experience will be a plus point here.

 

Job Description

 

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, 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

About Simpl
The thrill of working at a start-up that is starting to scale massively is something else. Simpl (FinTech startup of the year - 2020) was formed in 2015 by Nitya Sharma, an investment banker from Wall Street and Chaitra Chidanand, a tech executive from the Valley, when they teamed up with a very clear mission - to make money simple so that people can live well and do amazing things. Simpl is the payment platform for the mobile-first world, and we’re backed by some of the best names in fintech globally (folks who have invested in Visa, Square and Transferwise), and
has Joe Saunders, Ex Chairman and CEO of Visa as a board member.

Everyone at Simpl is an internal entrepreneur who is given a lot of bandwidth and resources to create the next breakthrough towards the long term vision of “making money Simpl”. Our first product is a payment platform that lets people buy instantly, anywhere online, and pay later. In
the background, Simpl uses big data for credit underwriting, risk and fraud modelling, all without any paperwork, and enables Banks and Non-Bank Financial Companies to access a whole new consumer market.
In place of traditional forms of identification and authentication, Simpl integrates deeply into merchant apps via SDKs and APIs. This allows for more sophisticated forms of authentication that take full advantage of smartphone data and processing power

Skillset:
 Workflow manager/scheduler like Airflow, Luigi, Oozie
 Good handle on Python
 ETL Experience
 Batch processing frameworks like Spark, MR/PIG
 File formats: parquet, JSON, XML, thrift, avro, protobuff
 Rule engine (drools - business rule management system)
 Distributed file systems like HDFS, NFS, AWS, S3 and equivalent
 Built/configured dashboards

Nice to have:
 Data platform experience for eg: building data lakes, working with near - realtime
applications/frameworks like storm, flink, spark.
 AWS
 File encoding types: Thrift, Avro, Protobuff, Parquet, JSON, XML
 HIVE, HBASE

Location: Bangalore
Work Timing: 5 Days A Week

Responsibilities include:
• Ensure right stakeholders gets right information at right time
• Requirement gathering with stakeholders to understand their data requirement
• Creating and deploying reports
• Participate actively in datamarts design discussions
• Work on both RDBMS as well as Big Data for designing BI Solutions
• Write code (queries/procedures) in SQL / Hive / Drill that is both functional and elegant,
following appropriate design patterns
• Design and plan BI solutions to automate regular reporting
• Debugging, monitoring and troubleshooting BI solutions
• Creating and deploying datamarts
• Writing relational and multidimensional database queries
• Integrate heterogeneous data sources into BI solutions
• Ensure Data Integrity of data flowing from heterogeneous data sources into BI solutions.

Minimum Job Qualifications:
• BE/B.Tech in Computer Science/IT from Top Colleges
• 1-5 years of experience in Datawarehousing and SQL
• Excellent Analytical Knowledge
• Excellent technical as well as communication skills
• Attention to even the smallest detail is mandatory
• Knowledge of SQL query writing and performance tuning
• Knowledge of Big Data technologies like Apache Hadoop, Apache Hive, Apache Drill
• Knowledge of fundamentals of Business Intelligence
• In-depth knowledge of RDBMS systems, Datawarehousing and Datamarts
• Smart, motivated and team oriented
Desirable Requirements
• Sound knowledge of software development in Programming (preferably Java )
• Knowledge of the software development lifecycle (SDLC) and models

Job Description:

We are looking for a Big Data Engineer who have worked across the entire ETL stack. Someone who has ingested data in a batch and live stream format, transformed large volumes of daily and built Data-warehouse to store the transformed data and has integrated different visualization dashboards and applications with the data stores.    The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them.

Responsibilities:

• Develop, test, and implement data solutions based on functional / non-functional business requirements.
• You would be required to code in Scala and PySpark daily on Cloud as well as on-prem infrastructure
• Build Data Models to store the data in a most optimized manner
• Identify, design, and implement process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Implementing the ETL process and optimal data pipeline architecture
• Monitoring performance and advising any necessary infrastructure changes.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Proactively identify potential production issues and recommend and implement solutions
• Must be able to write quality code and build secure, highly available systems.
• Create design documents that describe the functionality, capacity, architecture, and process.
• Review peer-codes and pipelines before deploying to Production for optimization issues and code standards

Skill Sets:

• Good understanding of optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies.
• Proficient understanding of distributed computing principles
• Experience in working with batch processing/ real-time systems using various open-source technologies like NoSQL, Spark, Pig, Hive, Apache Airflow.
• Implemented complex projects dealing with the considerable data size (PB).
• Optimization techniques (performance, scalability, monitoring, etc.)
• Experience with integration of data from multiple data sources
• Experience with NoSQL databases, such as HBase, Cassandra, MongoDB, etc.,
• Knowledge of various ETL techniques and frameworks, such as Flume
• Experience with various messaging systems, such as Kafka or RabbitMQ
• Creation of DAGs for data engineering
• Expert at Python /Scala programming, especially for data engineering/ ETL purposes

 

 

 

Must-Have:

• 5+ years of experience in software development.
• At least 2 years of relevant work experience on large scale Data applications
• Good attitude, strong problem-solving abilities, analytical skills, ability to take ownership as appropriate
• Should be able to do coding, debugging, performance tuning, and deploying the apps to Prod.
• Should have good working experience Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet)
• Kafka
• J2EE Frameworks (Spring/Hibernate/REST)
• Spark Streaming or any other streaming technology.
• Java programming language is mandatory.
• Good to have experience with Java
• Ability to work on the sprint stories to completion along with Unit test case coverage.
• Experience working in Agile Methodology
• Excellent communication and coordination skills
• Knowledgeable (and preferred hands-on) - UNIX environments, different continuous integration tools.
• Must be able to integrate quickly into the team and work independently towards team goals

Role & Responsibilities:

• Take the complete responsibility of the sprint stories’ execution
• Be accountable for the delivery of the tasks in the defined timelines with good quality
• Follow the processes for project execution and delivery.
• Follow agile methodology
• Work with the team lead closely and contribute to the smooth delivery of the project.
• Understand/define the architecture and discuss the pros-cons of the same with the team
• Involve in the brainstorming sessions and suggest improvements in the architecture/design.
• Work with other team leads to get the architecture/design reviewed.
• Work with the clients and counterparts (in US) of the project.
• Keep all the stakeholders updated about the project/task status/risks/issues if there are any.

We are looking for big data engineers to join our transformational consulting team serving one of our top US clients in the financial sector. You'd get an opportunity to develop big data pipelines and convert business requirements to production grade services and products. With
lesser concentration on enforcing how to do a particular task, we believe in giving people the opportunity to think out of the box and come up with their own innovative solution to problem solving.
You will primarily be developing, managing and executing handling multiple prospect campaigns as part of Prospect Marketing Journey to ensure best conversion rates and retention rates. Below are the roles, responsibilities and skillsets we are looking for and if you feel these resonate with you, please get in touch with us by applying to this role.
Roles and Responsibilities:
• You'd be responsible for development and maintenance of applications with technologies involving Enterprise Java and Distributed technologies.
• You'd collaborate with developers, product manager, business analysts and business users in conceptualizing, estimating and developing new software applications and enhancements.
• You'd Assist in the definition, development, and documentation of software’s objectives, business requirements, deliverables, and specifications in collaboration with multiple cross-functional teams.
• Assist in the design and implementation process for new products, research and create POC for possible solutions.
Skillset:
• Bachelors or Masters Degree in a technology related field preferred.
• Overall experience of 2-3 years on the Big Data Technologies.
• Hands on experience with Spark (Java/ Scala)
• Hands on experience with Hive, Shell Scripting
• Knowledge on Hbase, Elastic Search
• Development experience In Java/ Python is preferred
• Familiar with profiling, code coverage, logging, common IDE’s and other
development tools.
• Demonstrated verbal and written communication skills, and ability to interface with Business, Analytics and IT organizations.
• Ability to work effectively in short-cycle, team oriented environment, managing multiple priorities and tasks.
• Ability to identify non-obvious solutions to complex problems

We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Roles and Responsibilities:

• Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
• Develop programs in Scala and Python as part of data cleaning and processing.
• Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.  
• Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
• Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Provide high operational excellence guaranteeing high availability and platform stability.
• Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Skills:

• Experience with Big Data pipeline, Big Data analytics, Data warehousing.
• Experience with SQL/No-SQL, schema design and dimensional data modeling.
• Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
• Experience in designing systems that process structured as well as unstructured data at large scale.
• Experience in AWS/Spark/Java/Scala/Python development.
• Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
• Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
• Prior exposure to streaming data sources such as Kafka.
• Should have knowledge on Shell Scripting and Python scripting.
• High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
• Experience with NoSQL databases such as Cassandra / MongoDB.
• Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
• Experience building and deploying applications on on-premise and cloud-based infrastructure.
• Having a good understanding of machine learning landscape and concepts. 

 

Qualifications and Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.

Certifications:

Good to have at least one of the Certifications listed here:

    AZ 900 - Azure Fundamentals

    DP 200, DP 201, DP 203, AZ 204 - Data Engineering

    AZ 400 - Devops Certification

Responsibility: • Studied Computer Science, • 5+ years of software development experience, • Must have experience in Elasticsearch (2+ years experience is preferable), • Skills in Java, Python or Scala, • Passionate about learning big data, data mining and data analysis technologies, • Self-motivated; independent, organized and proactive; highly responsive, flexible, and adaptable when working across multiple teams, • Strong SQL skills, including query optimization are required. • Experience working with large, complex datasets is required, • Experience with recommendation systems and data warehouse technologies are preferred, • You possess an intense curiosity about data and a strong commitment to practical problem-solving, • Creative in thinking data centric products which will be used in online customer behaviors and marketing, • Build systems to pull meaningful insights from our data platform, • Integrate our analytics platform internally across products and teams, • Focus on performance, throughput, latency and drive these throughout our architecture. Bonuses -Experience with big data architectures such as Lambda Architecture. -Experience working with big data technologies (like Hadoop, Java Map/Reduce, Hive, Spark SQL), real-time processing frameworks (like Spark Streaming, Storm, AWS Kinesis). -Proficiency in key-value stores such as : HBase/Cassandra, Redis, Riak and MongoDB -Experience with AWS EMR

Description Deep experience and understanding of Apache Hadoop and surrounding technologies required; Experience with Spark, Impala, Hive, Flume, Parquet and MapReduce. Strong understanding of development languages to include: Java, Python, Scala, Shell Scripting Expertise in Apache Spark 2. x framework principals and usages. Should be proficient in developing Spark Batch and Streaming job in Python, Scala or Java. Should have proven experience in performance tuning of Spark applications both from application code and configuration perspective. Should be proficient in Kafka and integration with Spark. Should be proficient in Spark SQL and data warehousing techniques using Hive. Should be very proficient in Unix shell scripting and in operating on Linux. Should have knowledge about any cloud based infrastructure. Good experience in tuning Spark applications and performance improvements. Strong understanding of data profiling concepts and ability to operationalize analyses into design and development activities Experience with best practices of software development; Version control systems, automated builds, etc. Experienced in and able to lead the following phases of the Software Development Life Cycle on any project (feasibility planning, analysis, development, integration, test and implementation) Capable of working within the team or as an individual Experience to create technical documentation