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Bigdata Consultant with strong Scala exp
3 months ago
Bigdata Consultant with strong Scala exp
Location O`Fallon, MO (Day 1 Onsite)
Job Description:
- Strong People management, leadership, organizational skills. Outstanding communication (written and verbal) skills.
- Experience leveraging open-source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform basic analyses.
- Demonstrated basic knowledge of statistical analytical techniques, coding, and data engineering.
- Experience developing and configuring dashboards is a plus.
- Demonstrated judgement when escalating issues to the project team.
- High proficiency in Python/Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi), SQL.
- Curiosity, creativity, and excitement for technology and innovation.
- Demonstrated quantitative and problem-solving abilities.
- Expert proficiency in using Python/Scala, Spark (tuning jobs), SQL, Hadoop platforms to build Big Data products & platforms.
- Comfortable in developing shell scripts for automation.
- Proficient in standard software development, such as version control, testing, and deployment.
- Experience with visualization tools like tableau, looker.
- At least 5 years leading collaborative work in complex engineering projects in an Agile setting e.g. Scrum.
- Extensive data warehousing/data lake development experience with strong data modelling and data integration experience.
- Good SQL and higher-level programming languages with solid knowledge of data mining, machine learning algorithms and tools.
- Strong hands-on experience in Analytics & Computer Science.
- Demonstrated basic knowledge of statistical analytical techniques, coding, and data engineering.
- Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale in Java, Scala, or Python and deliver analytics involving all phases like data ingestion, feature engineering, modelling, tuning, evaluating, monitoring, and presenting.
- At least 10 years of relevant hands-on experience as a Data Engineer in an individual contributor capacity.
- Able to lead the implementation of machine learning production systems.
- Demonstrated ability, through hands-on experience, to develop production machine learning pipelines.
