Data Engineer - Data platform - Data Science

experience: 5 to 10 yrs

location: bangalore

immediate joiners preferred

 

Demand #1 Data Engineer (Platform)

 

Role Responsibilities/Skills

• Develop, understand, and enhance code in traditional data warehouse environments, data lake, and cloud environments like Snowflake, Azure, Databricks

• Build new end-to-end business intelligence solutions- data extraction, ETL processes applied on data to derive useful business insights, and best representing this data through dashboards.

• Write complex SQL queries used to transform data using Python/Unix shell scripting

• Understand business requirements and create visual reports and dashboards using Power BI or Tableau.

• Upskill to different technologies, understand existing products and programs in place

• Work with other development and operations teams.

• Flexible with shifts and occasional weekend support. Key Competencies

• Full life-cycle experience on enterprise software development projects.

• Experience in relational databases/ data marts/data warehouses and complex SQL programming.

• Extensive experience in ETL, shell or python scripting, data modelling, analysis, and preparation

• Experience in Unix/Linux system, files systems, shell scripting.

• Good to have knowledge on any cloud platforms like AWS, Azure, Snowflake, etc.

• Good to have experience in BI Reporting tools – Power BI or Tableau

• Good problem-solving and analytical skills used to resolve technical problems.

• Must possess a good understanding of business requirements and IT strategies.

• Ability to work independently but must be a team player. Should be able to drive business decisions and take ownership of their work.

• Experience in presentation design, development, delivery, and good communication skills to present analytical results and recommendations for action-oriented data driven decisions and associated operational and financial impacts. Required/Preferred Skills

• RDBMS and Data Warehousing (Required)

• SQL Programming and ETL (Required)

• Unix/Linux shell scripting (Required)

• Power BI / Tableau (Preferred)

• Python, Scala, Java (Preferred)

• Cloud Platforms - Azure, Snowflake, Databricks, Datalake (Preferred)

Demand # 4 Data Engineer - Data Science

Responsibilities/Skills:

Full Stack Development background with Java and JavaScript/CSS/HTML 

Knowledge of ReactJs/Angular is a plus 

Big Data Engineer with solid background with the larger Hadoop ecosystem and real-time analytics tools including PySpark/Scala-Spark/Hive/Hadoop CLI/MapReduce/Storm/Kafka/Lambda Architecture Comfortable with using the larger Hadoop eco system 

Familiar with job scheduling challenges in Hadoop 

Experienced in creating and submitting Spark jobs 

Experienced with Kafka/Storm and real-time analytics Core Java and Python/Scala background and their related libraries and frameworks 

Experienced with Spring Framework and Spring Boot Unix/Linux expertise; comfortable with Linux operating system and Shell Scripting PL/SQL, RDBMS background with Oracle/MySQL 

Familiarity with ORMs a plus Design, Development, Configuration, Unit and Integration testing of web applications to meet business process and application requirements 

Familiar with config management/automations tools such as Ansible/Chef/Puppet 

Comfortable with Microservices, CI/CD, Dockers, and Kubernetes 

Familiarity with AT&T’s ECO platform is a plus 

Comfortable tweaking/using Jenkins and deployment orchestration Creating/modifying Dockers and deploying them via Kubernetes