Lead Data Engineer (Azure)

Being part of Data Engineering means you’ll be part of a team that focuses on extending our network superiority to enable the continued execution of our digital strategy. With us, you’ll be working with world-leading technology and change the way we do IT to ensure business needs drive priorities, accelerating our digitisation programme. 

We are seeking a highly skilled Data Engineer with expertise in Spark, Python, Scala. The successful candidate will be responsible for will be responsible for designing, developing, and maintaining data pipelines using Spark, Python, Scala, and related technologies. The Data Engineer will also be responsible for ensuring data quality, data security, and optimal performance of the data pipelines. Any new engineer would be mostly into developing reusable data processing and storage frameworks that can be used across data platform. 

Hadoop Data Engineering – Hive, Oozie, Yarn / MapReduce, Spark (must) with SCALA (Pref) or Python, Strong SQL.

Job Location – Bangalore

Key Responsibilities

Data Engineer Senior Specialist role is to coordinate, and execute all activities related to the requirements interpretation, design, and implementation of Data Analytics applications. This individual will apply proven industry and technology experience as well as communication skills, problem-solving skills, and knowledge of best practices to issues related to design, development, and deployment of mission-critical systems with a focus on quality application development and delivery.

This role is key to the success of the Data Engineering capability at Telstra and will be responsible and accountable for the following:

Lead the design, development, and maintenance of data pipelines using Spark, Python, Scala, and related technologies.
Work with high volume data and ensure data quality and accuracy.
Implement data security and privacy best practices to protect sensitive data.
Collaborate with data scientists and business stakeholders to understand data needs and requirements.
Develop and maintain documentation on data pipeline architecture, data models, and data workflows.
Mentor and provide technical guidance to junior team members.
Monitor and troubleshoot data pipelines to ensure they are performing optimally.
Stay up to date with the latest developments in Azure, AWS, Spark, Python, Scala, and related technologies and apply them to solve business problems.
Optimize data pipelines for cost and performance.
Automate data processing tasks and workflows to reduce manual intervention.
Ability to work in Agile Feature teams.
Provide training and educate other team members around core capabilities and helps them deliver high quality solutions and deliverables/documentation.
Self-Motivator to perform Design / Develop user requirements, test and deploy the changes into production.

Technical Skills
Hands-on experience in the following on Spark Core, Spark SQL, SQL/Hive/Impala.
Data engineer with expertise of working on Azure Cloud using Databricks, Kinesis/ Azure Event hub Flume/Kafka/Spark streaming, Azure Data Factory.
Exposure on Hadoop Ecosystem (HDP/Cloudera/MapR/EMR etc)
Experience of working on File formats (Parquet/ORC/AVRO/Delta/Hudi etc.)
Experience with high volume data processing and data streaming technologies
Experience of using Orchestration tools like Control-m, Azure Data Factory,Airflow,Luigi to schedule jobs.
Demonstrated experience leading data engineering projects and mentoring junior team members.
Strong experience in data modelling, schema design, and ETL development using SQL and related technologies.
Familiarity with data security and privacy best practices
Good exposure on TDD
Exposure on using CI tools like Git, Bitbucket, Github, Gitlab, Azure DevOps
Exposure on using CD tools like Jenkins, Bamboo, Azure DevOps
Exposure on Observability tools like Azure Monitor, Graphana etc
Prior experience in building or working in team building reusable frameworks
Good understanding of Data Architecture and design principles. (Delta/Kappa/Lambda architecture)
Exposure to Code Quality – Static and Dynamic code scans
Experience in designing solutions for multiple large data warehouses with a good understanding of cluster and parallel architecture as well as high-scale or distributed RDBMS and/or knowledge on NoSQL platforms.
Should be able to provide scalable and robust solution architecture depending on the business needs.
Propose best practices/standards!
Programming & Databases – Java /Python/Scala/ SQL Procedure. Multi tenanted databases / Spark