Data Engineer

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Location: Kolkata (India)

Job Description:

Functions and Responsibilities:

  • Create functional & technical documentation – e.g. Data pipelines, source to target mappings, ETL specification documents, run books
  • Build data pipelines, apply automation in data integration and management, tracking data consumption patterns, performing intelligent sampling and caching
  • Tests, debugs, and documents Pipelines and data integration processes, SQL and/or no-SQL queries

Qualifications and Preferred Skills:

  • Strong experience with advanced analytics tools for Object-oriented/object function scripting using languages such as [R, Python, Java, Scala, others].
  • Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management. The ability to work with both IT and business in integrating analytics and data science output into business processes and workflows.
  • Strong experience with popular database programming languages including [SQL, PL/SQL, others] for relational databases and certifications on upcoming [NoSQL/Hadoop oriented databases like HBase, Cassandra, others] for nonrelational databases.
  • Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include ETL/ELT, data replication/CDC, message-oriented data movement, API design and access and upcoming data ingestion and integration technologies such as stream data integration, CEP and data virtualization.
  • Strong experience in working with SQL on Hadoop tools and technologies including [HIVE, Impala, Presto, others] from an open source perspective and [Hortonworks Data Flow (HDF), Talend, others] from a commercial vendor perspective.
  • Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production.
  • Basic experience working with popular data discovery, analytics and BI software tools like Sisense, Tableau, Qlik, PowerBI and others for semantic-layer-based data discovery.
  • Strong experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms.
  • Basic understanding of popular open-source and commercial data science platforms such as [Python, R, KNIME, Alteryx, others] is a strong plus but not required/compulsory.
  • Demonstrated ability to work across multiple deployment environments including [cloud, on-premises and hybrid], multiple operating systems.
  • Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data managers and consumers across an organization
  • Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.
  • Strong experience supporting and working with cross-functional teams in a dynamic business environment.

Education and Certification Requirements:

  • A bachelor’s or master’s degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field [or equivalent work experience] is required.
  • Advance degree in computer science, statistics, applied mathematics is preferred.
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