Senior Data Engineer (Remote)

Published date Posted on Indeed on Nov 18, 2021 (18 d ago)

Must be able to write quality code and build secure, highly available systems.

  • Assemble large, complex data sets that meet functional / non-functional business requirements.

  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc with the guidance.

  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

  • Monitoring performance and advising any necessary infrastructure changes.

  • Defining data retention policies.

  • Implementing the ETL process and optimal data pipeline architecture

  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.

  • Create design documents that describe the functionality, capacity, architecture, and process.

  • Develop, test, and implement data solutions based on finalized design documents.

  • Work with data and analytics experts to strive for greater functionality in our data systems.

  • Proactively identify potential production issues and recommend and implement solutions


  • Good understanding of optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

  • Proficient understanding of distributed computing principles

  • Experience in working with batch processing/ real-time systems using various open-source technologies like NoSQL, Spark, Pig, Hive, Apache Airflow.

  • Implemented complex projects dealing with the considerable data size (PB).

  • Optimization techniques (performance, scalability, monitoring, etc.)

  • Experience with integration of data from multiple data sources

  • Experience with NoSQL databases, such as HBase, Cassandra, MongoDB, etc.,

  • Knowledge of various ETL techniques and frameworks, such as Flume

  • Experience with various messaging systems, such as Kafka or RabbitMQ

  • Good understanding of Lambda Architecture, along with its advantages and drawbacks

  • Creation of DAGs for data engineering

  • Expert at Python /Scala programming, especially for data engineering/ ETL purposes

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