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High-Performance Data Architect
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We are re-thinking our approach to delivering data solutions and planning for a phased transition to more efficient and effective data management practices. Our goal is to find a skilled Data Engineer who can help us meet these evolving data needs.
Main Responsibilities- Design and implement data flows for big data/data lake use cases, ensuring scalability and efficiency.
- Develop a comprehensive understanding of full life cycle of data management principles, including Data Governance, Architecture, Modelling, Storage, Security, Master data, and Quality.
- Collaborate with analytics and business stakeholders to improve data models that feed BI tools, increasing data accessibility, and fostering data-driven decision making across the organization.
- Work with team of data engineers to deliver tasks and achieving weekly and monthly goals, also guiding the team to follow best practices and improve deliverables.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
- Responsible for estimating the cluster size, core size, monitoring, and troubleshooting of the data bricks cluster and analysis server to produce optimal capacity for computing data ingestion.
- Deliver master data cleansing and improvement efforts; including automated and cost-effective solutions for processing, cleansing, and verifying the integrity of data used for analysis.
- Expertise in securing the big data environment including encryption, tunnelling, access control, secure isolation.
- To guide and build highly efficient OLAP cubes using data modelling techniques to cater all the required business cases and mitigate the limitation of Power BI in analysis service.
- Deploy and maintain highly efficient CI/CD devops pipelines across multiple environments such as dev, stg and production.
- Strictly follow scrum based agile approach of development to work based on allocated stories.
- Comprehensive knowledge on data extraction, Transformation and loading data from various sources like Oracle, Hadoop HDFS, Flat files, JSON, Avro, Parquet and ORC.
- Experience defining, implementing, and maintaining a global data platform.
- Experience building robust and impactful data visualisation solutions and gaining adoption.
- Extensive work experience onboarding various data sources using real-time, batch load or scheduled loads. The sources can be in cloud, on premise, SQL DB, NO SQL DB or API-based.
- Expertise in extracting the data through JSON, ODATA, REST API, WEBSERVICES, XML.
- Expertise in data ingestion platforms such as Apache Sqoop, Apache Flume, Amazon kinesis, Fluent, Logstash etc.
- Hands on experience in using Databricks, Pig, SCALA, HIVE, Azure Data Factory, Python, R.
- Operational experience with Big Data Technologies and Engines including Presto, Spark, Hive and Hadoop Environments.
- Experience in various databases including Azure SQL DB, Oracle, MySQL, Cosmos DB, MongoDB.
- Bachelor's degree (masters' preferred) in Computer Science, Engineering, or any other technology related field.
- 10+ years of experience in data analytics platform and hands-on experience on ETL and ELT transformations with strong SQL programming knowledge.
- 5+ years of hands-on experience on big data engineering, distributed storage and processing massive data into data lake using Scala or Python.
- Proficient knowledge on Hadoop and Spark eco systems like HDFS, Hive, Sqoop, Oozie, Spark core, streaming.
- Experience with programming languages such as Scala, Java, Python and Shell scripting.
- Proven Experience in pulling data through REST API, ODATA, XML,Web services.
- Experience with Azure product offerings and data platform.
- Experience in data modelling (data marts, snowflake/Star, Normalization, SCD2).
- Architect and defining the data flows and building highly efficient, scalable data pipelines.
- To work in tandem with the Enterprise and Domain Architects to understand the business goals and vision, and to contribute to the Enterprise Roadmaps.
- Strong troubleshooting skills, problem solving skills of any issues stopping business progress.
- Coordinate with multiple business stake holders to understand the requirement and deliver.
- Conducting a continuous audit of data management system performance, refine whenever required, and report immediately any breach or loopholes to the stakeholders.
- Allocate task to various team members, track the status and provide the report on activities to management.
- Understand the physical and logic plan of execution and optimize the performance of data pipelines.
- Extensive background in data mining and statistical analysis.
- Able to understand various data structures and common methods in data transformation.
- Ability to work with ETL tools with strong knowledge on ETL concepts.
- Strong focus on delivering outcomes.
- Data management: modelling, normalization, cleaning, and maintenance.
- Understand Data architectures, Data warehousing principles and be able to participate in the design and development of conventional data warehouse solutions.
