Create and maintain optimal data pipeline architecture.
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ?big data? technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Keep data secure
Create data tools for analytics and data scientist team members
Work with data and analytics experts to strive for greater functionality data systems
Typical skills and background:SKILLS:
Experience of development of ETLs using Informatica BDM and Power Center
Knowledge in data architecture, defining data retention policies, monitoring performance and advising any necessary infrastructure changes
Solid development skills in Java, Scala and SQL
Good knowledge of working with different Hadoop based services like Hive, Impala, Kudu, HBase, Kafka, Flume, Sqoop, Oozie etc.
Clear hands-on mastery in big data systems - Hadoop ecosystem, Cloud technologies (AWS, Azure, Google), in-memory database systems (HANA, Hazel cast, etc) and other database systems - traditional RDBMS (Terradata, SQL Server, Oracle), and NoSQL databases (Cassandra, MongoDB, DynamoDB)
EXPERIENCE AND QUALIFICATION:
Bachelors degree in Computer Science or equivalent; Masters preferred
Minimum of 6 years hands-on experience with a strong data background
Extensive experience working with Big Data tools and building data solutions for advanced analytics
Practical knowledge across data extraction and transformation tools - traditional ETL tools (Informatica, Altryx) as well as more recent big data tools
