Data Engineer – Saint Louis, MO -Hybrid Position
Hi,
Job Title: Sr. Data Engineer ( 12+ Years is a must)
Duration: Long Term Contract.
Location: St Louis, MO ( In Person 2 days Preferred, Remote Okay if candidate is exceptional)
Must Have : Strong in Scala and Spark
12+ Years experience is a must
As a Senior Data Engineer in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data.
You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like building ML models, automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Spark, R, etc.
Your Role
Drive the evolution of Data & Services products/platforms with an impact-focused on data science and engineering
Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
Ensuring that algorithms generate accurate user recommendations.
Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
Provide support for deployed data applications and analytical models by being a trusted advisor to Data Scientists and other data consumers by identifying data problems and guiding issue resolution with partner Data Engineers and source data providers.
Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
Discover, ingest, and incorporate new sources of real-time, streaming, batch, and API-based data into our platform to enhance the insights we get from running tests and expand the ways and properties on which we can test
Experiment with new tools to streamline the development, testing, deployment, and running of our data pipelines.
Maintain awareness of relevant technical and product trends through self-learning/study, training classes and job shadowing.
Participate in the development of data and analytic infrastructure for product development
Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations
Partner with roles across the organization including consultants, engineering, and sales to determine the highest priority problems to solve
Evaluate trade-offs between many possible analytics solutions to a problem, taking into account usability, technical feasibility, timelines, and differing stakeholder opinions to make a decision
Break large solutions into smaller, releasable milestones to collect data and feedback from product managers, clients, and other stakeholders
Evangelize releases to users, incorporating feedback, and tracking usage to inform future development
Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
Work with small, cross-functional teams to define the vision, establish team culture and processes
Consistently focus on key drivers of organization value and prioritize operational activities accordingly
Escalate technical errors or bugs detected in project work
Maintain awareness of relevant technical and product trends through self-learning/study, training classes, and job shadowing.
Ideal Candidate Qualifications
Superior academic record at a leading national university in Computer Science, Data Science, Computer Engineering, Technology, or a related field or equivalent work experience
Expertise in Data Engineering and implementing multiple end-to-end DW projects in Big Data environment
At least 5 years of experience as a data engineer or machine learning engineer and with open-source tools
Prior experience in working in product development/management role
Experience in building and deploying production level data driven applications and data processing workflows/pipelines
Experience with application development frameworks (Java/Scala, Spring)
Experience with data processing and storage frameworks like Hadoop, Spark, Kafka
Experience implementing REST services with support for JSON, XML and other formats
Experience with performance Tuning of Database Schemas, Databases, SQL, ETL Jobs, and related scripts
Experience of working in Agile teams
Good analytical skills required for writing and performance tuning complex SQL queries, debugging production issues, providing root cause, and implementing mitigation plan
Ability to quickly learn and implement new technologies, and perform POC to explore best solution for the problem statement
Flexibility to work as a member of a matrix based diverse and geographically distributed project teams
Strong project management skills
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, modeling, tuning, evaluating, monitoring, and presenting
Curiosity, creativity, and excitement for technology and innovation
Demonstrated quantitative and problem-solving abilities
Ability to multi-task and strong attention to detail
Motivation, flexibility, self-direction, and desire to thrive on small project teams
Good communication skills – both verbal and written – and strong relationship, collaboration skills, and organizational skills
The following skills will be considered as a plus
Financial Institution or a Payments experience a plus
Batch processing and workflow tools such as NiFi
Experience in developing integrated cloud applications with services like Azure, Databricks, AWS or GCP
Experience in managing/working in Agile teams
Experience developing and configuring dashboards
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