AWS Simple Queuing Service (SQS) Jobs in Hyderabad

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

Roles and Responsibilities

Big Data Engineer + Spark Responsibilies Atleast 3 to 4 years of relevant experience as Big Data Engineer Min 1 year of relevant hands-on experience into Spark framework. Minimum 4 years of Application Development experience using any programming language like Scala/Java/Python. Hands on experience on any major components in Hadoop Ecosystem like HDFS or Map or Reduce or Hive or Impala. Strong programming experience of building applications / platforms using Scala/Java/Python. Experienced in implementing Spark RDD Transformations, actions to implement business analysis. An efficient interpersonal communicator with sound analytical problemsolving skills and management capabilities. Strive to keep the slope of the learning curve high and able to quickly adapt to new environments and technologies. Good knowledge on agile methodology of Software development.

Skills

Atleast 3 to 4 years of relevant experience as Big Data Engineer Min 1 year of relevant hands-on experience into Spark framework. Minimum 4 years of Application Development experience using any programming language like Scala/Java/Python. Hands on experience on any major components in Hadoop Ecosystem like HDFS or Map or Reduce or Hive or Impala. Strong programming experience of building applications / platforms using Scala/Java/Python. Experienced in implementing Spark RDD Transformations, actions to implement business analysis.

Airflow developer:

Exp: 5 to 10yrs & Relevant exp must be above 4 Years.

Work location: Hyderabad (Hybrid Model)

Job description:  

·        Experience in working on Airflow.

·        Experience in SQL, Python, and Object-oriented programming. 

·        Experience in the data warehouse, database concepts, and ETL tools (Informatica, DataStage, Pentaho, etc.).

·        Azure experience and exposure to Kubernetes. 

·        Experience in Azure data factory, Azure Databricks, and Snowflake. 

Required Skills: Azure Databricks/Data Factory, Kubernetes/Dockers, DAG Development, Hands-on Python coding.

What are the Key Responsibilities:

• Design NLP applications
• Select appropriate annotated datasets for Supervised Learning methods
• Use effective text representations to transform natural language into useful features
• Find and implement the right algorithms and tools for NLP tasks
• Develop NLP systems according to requirements
• Train the developed model and run evaluation experiments
• Perform statistical analysis of results and refine models
• Extend ML libraries and frameworks to apply in NLP tasks
• Remain updated in the rapidly changing field of machine learning

What are we looking for:

• Proven experience as an NLP Engineer or similar role
• Understanding of NLP techniques for text representation, semantic extraction techniques, data structures, and modeling
• Ability to effectively design software architecture
• Deep understanding of text representation techniques (such as n-grams, a bag of words, sentiment analysis etc), statistics and classification algorithms
• Knowledge of Python, Java, and R
• Ability to write robust and testable code
• Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like sci-kit-learn)
• Strong communication skills
• An analytical mind with problem-solving abilities
• Degree in Computer Science, Mathematics, Computational Linguistics, or similar field

Roles and Responsibilities

Data Engineer 

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 

Big Data Engineer: 5+ yrs.
Immediate Joiner

• Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
• Experience in developing lambda functions with AWS Lambda
• Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
• Should be able to code in Python and Scala.
• Snowflake experience will be a plus
• We can start keeping Hadoop and Hive requirements as good to have or understanding of is enough rather than keeping it as a desirable requirement.

Big data Developer

Exp: 3yrs to 7 yrs.
Job Location: Hyderabad
Notice: Immediate / within 30 days

1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
2. Experience in developing lambda functions with AWS Lambda
3. Expertise with Spark/PySpark Candidate should be hands on with PySpark code and should be able to do transformations with Spark
4. Should be able to code in Python and Scala.
5. Snowflake experience will be a plus

We can start keeping Hadoop and Hive requirements as good to have or understanding of is enough rather than keeping it as a desirable requirement.

Indium Software is a niche technology solutions company with deep expertise in Digital , QA and Gaming. Indium helps customers in their Digital Transformation journey through a gamut of solutions that enhance business value.

With over 1000+ associates globally, Indium operates through offices in the US, UK and India

Visit www.indiumsoftware.com to know more.

Job Title: Analytics Data Engineer

What will you do:
The Data Engineer must be an expert in SQL development further providing support to the Data and Analytics in database design, data flow and analysis activities. The position of the Data Engineer also plays a key role in the development and deployment of innovative big data platforms for advanced analytics and data processing. The Data Engineer defines and builds the data pipelines that will enable faster, better, data-informed decision-making within the business.

We ask:

Extensive Experience with SQL and strong ability to process and analyse complex data

The candidate should also have an ability to design, build, and maintain the business’s ETL pipeline and data warehouse The candidate will also demonstrate expertise in data modelling and query performance tuning on SQL Server
Proficiency with analytics experience, especially funnel analysis, and have worked on analytical tools like Mixpanel, Amplitude, Thoughtspot, Google Analytics, and similar tools.

Should work on tools and frameworks required for building efficient and scalable data pipelines
Excellent at communicating and articulating ideas and an ability to influence others as well as drive towards a better solution continuously.
Experience working in python, Hive queries, spark, pysaprk, sparkSQL, presto

• Relate Metrics to product
• Programmatic Thinking
• Edge cases
• Good Communication
• Product functionality understanding

Perks & Benefits:
A dynamic, creative & intelligent team they will make you love being at work.
Autonomous and hands-on role to make an impact you will be joining at an exciting time of growth!

Flexible work hours and Attractive pay package and perks
An inclusive work environment that lets you work in the way that works best for you!