almabetter

Data Engineer, Products and Platform Data Engineering

Atlassian, Bengaluru, Karnataka

Remote3 years expData SciencePermanent

26 Jul, 2024

Skills:

PythonJavaSparkAirflowAWS data services (RedshiftAthenaEMR)Apache projects (SparkFlinkHiveKafka)relational databasesSQL

Overview

Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

You will be part of a world-class Data Engineering team, where you will:

  • influence product teams
  • inform Data Science and Analytics Platform teams
  • partner closely with data consumers and producers to ensure quality and usefulness of data assets

You will be involved in strategizing measurement, collecting data, and generating insights.

This work will help understand and improve product experience and engagement, optimize efficiency and costs, and drive strategy.

Responsibilities

Data Engineering is a multi-faceted role, where you can have focused or broad set of responsibilities, including:

  • Defining metrics
  • Instrumenting logging
  • Acquiring/ingesting data
  • Architecting & modeling data
  • Transforming data
  • Ensuring data quality, governance, and enablement
  • Alerting, visualization, and reporting
  • Developing at scale and improving efficiency
  • Working autonomously and adding perspective to the team

Qualifications

  • BE in Computer Science or equivalent experience with 3+ years as a Data Engineer or a similar role
  • Programming skills in Python & Java (good to have)
  • Design data models for storage and retrieval to meet product and requirements
  • Build scalable data pipelines using Spark, Airflow, AWS data services (Redshift, Athena, EMR), Apache projects (Spark, Flink, Hive, and Kafka)
  • Familiar with modern software development practices (Agile, TDD, CICD) applied to data engineering
  • Enhance data quality through internal tools/frameworks detecting DQ issues. Working knowledge of relational databases and SQL query authoring
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