Senior Data Quality Engineer

Responsibilities: • Be responsible for data product testing and quality of deliverables on the project • Data quality implementation and improving data quality as main goal • Establish data testing approach and test design, data quality checks across the data lifecycle • Work on priorities to achieve better data quality on the project within tight schedule • Identify key stakeholders, and work with them along with the team to educate them, advocate quality and improve it on the project Requirements: • 5 years of experience in data and analytics domain • Experience working within large team, communication with business and tech team, ability to estimate and take responsibility for deliverables • Solid knowledge of testing, data quality and data governance. Data-oriented personality. • Familiarity with data ingestion pipeline concepts, data technologies such as OLTP databases, Data Warehousing, Data Lakes, DWBI tools. • Understanding and working within modern SDLC practices in data processing • Ability to take ownership and lead a team of professionals to achieve excellence in delivery • Strong communication skills. Ability to manage customer expectations, present and explain project deliverables to senior stakeholders Proficiency and experience: • Strong SQL knowledge (ANSI and flavors), experience with different RDBMS • NoSQL databases (e.g. Cassandra, HBase, MongoDB) • Big Data - Hadoop, HDFS, Hive, Spark, Kafka, Flume, Sqoop; • Data pipelines and ETL (e.g. SSIS), Data Visualization (e.g. PowerBI, Tableau, Tibco Spotfire) • Expert data wrangling, data masking, creating a valid test data set • Master Data Management, Data Quality, and Data Governance • Programming languages like Python, Java/Scala, Bash scripting • Cloud (AWS/Azure/GCP) – Storage, Compute, Networking • CI / CD principles and tools (e.g. Jenkins)