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Data Engineering Lead

Chicago, IL, United States

Alexa Translations provides translation services in the legal, financial, and securities sectors by leveraging proprietary A.I. technology and a team of highly specialized linguistic experts. We are seeking a talented and experienced Data Team Lead to oversee our data team's operations. The ideal candidate will have a strong background in data collection, cleaning, and management, with a focus on bilingual data. The Data Team Lead will play a key role in ensuring that our AI engine is trained on the most relevant and accurate data, ultimately enhancing the quality of our translation services.

Responsibilities:

Leading and managing a team of data specialists responsible for crawling domain-specific bilingual data for training our AI engine.

Developing and implementing data collection strategies to ensure the acquisition of high-quality bilingual data sets.

Overseeing the cleaning and preprocessing of crawled data to remove noise and ensure accuracy.

Collaborating with other teams, such as engineering and linguistics, to understand data requirements and optimize data collection processes.

Monitoring data quality and performance metrics, identifying areas for improvement and implementing solutions.

Staying up-to-date with industry trends and best practices in data collection, cleaning, and management.

Responsible for the design, deployment, and maintenance of the business’s data platforms.

Owning and extending the business’s data pipeline through the collection, storage, processing, and transformation of large data sets.

Participating in the design, and providing insights and guidance on database technology and data modeling best practices.

Developing and managing scalable data processing platforms used for exploratory data analysis and real-time analytics

Building a metadata system where all available data is maintained and cataloged.

Developing ETL processes that convert data into formats through a team of data analysts and dashboard charts.

Retrieving and analyzing data through the use of SQL, and Excel, among other data management systems

Building data loading services for the purpose of importing data from numerous disparate data sources, inclusive of APIs, logs, relational, and non-relational databases

Development of reliable data pipelines that translate raw data into powerful useful data points.

Design, architect, implements and support key datasets that avail structured and timely access to actionable business insight

Qualifications:

Bachelor's degree (Master's Degree is an advantage) in Computer Science, Data Science, or a related field.

At least 3 years of working experience working in a data engineering department, preferably as a Senior Data Engineer in a fast-paced environment and complex business setting.

Experience in data collection, cleaning, and management, preferably in a linguistic or translation-related field.

Fluency in English (French is an advantage), with excellent written and verbal communication skills in both languages.

Strong analytical and problem-solving skills, with the ability to work with large and complex data sets.

Extensive hands-on experience with data crawling tools (Scrapy, etc) and techniques, should be able to develop customized crawlers.

Demonstrated experience in building and maintaining reliable and scalable ETL on big data platforms as well as experience working with varied forms of data infrastructure inclusive of relational databases such as SQL and Spark.

Experience in data warehousing inclusive of dimensional modeling concepts and demonstrating proficiency in scripting languages, for example, Python, Perl, and so forth

Deep knowledge of data mining techniques, and relational, and non-relational databases.

Sound understanding of building complex ETL pipelines using either open-source tools such as mage, Luigi and airflow or cloud-based solutions such as AWS Glue.

Highly proficient in the use of MS Office products ( Word, Excel, PowerPoint)

Ability to perform complex data analyses with large data volumes.

Strong knowledge in Linux, OS tools, and file-system level troubleshooting.

Substantial experience working with big data infrastructure tools such as Python, SQS, and Redshift.

A suitable candidate will also be proficient in Scala, Spark, Spark Streaming, AWS

Result-driven individual, passionate and a self-starter, proactive requiring minimal supervision

Proven leadership abilities, with a track record of successfully leading teams and driving results.

Familiarity with machine learning concepts and techniques is a plus.

Preferred Qualifications

Working knowledge with CAT Tools such as: memoQ, SDL, Memsource

Desire to continue to grow professional capabilities with ongoing training and educational opportunities

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