Evaluate, implement and recommend Big Data technology stack that would align with companys technology on AWS.
Drive significant technology initiatives end to end and across multiple layers of data and analytics engineering.
Ability to evangelize next generation infrastructure in analytics space (Batch, Near Realtime, Realtime technologies) on AWS cloud.
Passionate for continuous learning, experimenting, applying the open-source technologies and software paradigms.
Enrich and refine the backlog by working closely with engineering managers and delivery leads of the academic publishing business domains.
Managing the dependencies across the team, setting the expectations and working towards addressing various goals and OKRs.
Work closely with several data engineering scrum teams and manage day-to-day chores.
Eager to assure quality by a helping in developing a strong validation and verification checks in the data engineering solutions.
Provides strong technical expertise in adopting and contributing to open-source technologies related to Bigdata and analytics.
Define and Drive best practices.
Be a role model to data engineers pursuing technical career path in engineering.Qualifications

What we are looking for

Minimum of 8+ years of overall experience including but not limited to architect, design and development using various database technologies.
A minimum 4+ years of hands-on association with AWS Analytical services and big data stack.
Ability to Design and build High Availability architecture.
Ability to successfully lead a team of data engineers, data evangelists, stewards and business analysts through all phases of the data engineering life cycle.
Active in the community in terms of articles / blogs / speaking engagements at conferences - this is an added big advantage.
Big advantage will be for having experience in presenting data using: PowerBI/ Tableau/Quick Sight.
Knowledge in a variety of machine learning is an added advantage.
Excellent written and verbal communication skills for coordinating across teams.
The ideal candidate is someone with the following:
- Experience using Cloud technologies: AWS Athena, Glue, EMR, Lake formation, RDS, Redshift, S3, Kinesis, Data pipelines etc.
- Experience querying databases both SQL and No-SQL.
- Coding knowledge and experience with several Python/Java/Scala, etc.
- Experience analysing data from 3rd party providers: Google Analytics, Facebook Insights, etc.
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.

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