Tiger Analytics

Principal Data Engineer (Azure and Databricks)

DALLAS, TXPosted 24 days ago

Job summary

  • Job post source

    This job is directly from Tiger Analytics

  • Job overview

    The Principal Data Engineer (Azure and Databricks) at Tiger Analytics leads the design and development of scalable data ingestion pipelines and analytics solutions using Azure cloud technologies, impacting global AI and analytics projects.

  • Responsibilities and impact

    The role involves building metadata-driven data pipelines, processing structured and unstructured data, scheduling and monitoring pipelines, collaborating with cross-functional teams, and making technology decisions to deliver analytical solutions.

  • Compensation and benefits

    The compensation packages are among the best in the industry, with significant career development opportunities in a fast-growing entrepreneurial environment and a high degree of individual responsibility.

  • Experience and skills

    Candidates must have hands-on experience with Azure Data Factory, PySpark, Databricks, ADLS, and Azure SQL Database, strong programming skills in SQL, Python, or Scala/Java, and familiarity with big data technologies like Hadoop, Spark, and Kafka; certifications like DP-203 or Databricks Certified Developer are valuable.

  • Career development

    The position offers excellent career growth opportunities in a challenging and fast-growing entrepreneurial setting with high individual responsibility.

  • Work environment and culture

    Tiger Analytics fosters a culture of expertise, respect, and a team-first mindset, supporting a global remote workforce and being Great Place to Work-Certified™.

  • Company information

    Tiger Analytics is a global AI and analytics consulting firm headquartered in Silicon Valley with delivery centers worldwide, known for innovative AI solutions impacting millions globally.

  • Job location and travel

    The company has offices in multiple countries including India, the US, UK, Canada, and Singapore, with a substantial remote global workforce.

  • Unique job features

    The job offers the chance to work at the forefront of AI with cutting-edge cloud and big data technologies, engaging in innovative projects involving data lakes, lakehouse architectures, and real-time data processing.

Company overview

Tiger Analytics is a leading provider of data science and advanced analytics solutions, helping businesses leverage data to drive better decision-making. The company specializes in AI, machine learning, and big data technologies to offer customized analytics services across various industries such as retail, finance, and healthcare. Founded in 2011, Tiger Analytics has grown rapidly, establishing a global presence with offices in the United States, India, and Singapore. Their revenue model primarily revolves around consulting fees and long-term analytics partnerships with clients. Notably, the company has been recognized for its innovative solutions and has received several industry accolades.

How to land this job

  • Tailor your resume to emphasize hands-on experience with Azure Data Factory, Databricks, ADLS, and Azure SQL Database, highlighting your ability to design scalable, metadata-driven data ingestion pipelines for batch and streaming datasets.

  • Showcase your proficiency in programming languages such as SQL, Python, Scala, or Java, along with your debugging and unit testing skills, to align with the role's technical demands.

  • Apply through multiple platforms including Tiger Analytics' official corporate careers page and LinkedIn to maximize your application visibility and reach.

  • Connect with current employees or team members in Tiger Analytics' data engineering or cloud solutions divisions on LinkedIn; start conversations by referencing recent Azure or Databricks projects they’ve shared or expressing interest in their approach to data lake or lakehouse architectures.

  • Optimize your resume for ATS by incorporating keywords from the job description like 'Azure Data Factory,' 'Databricks,' 'PySpark,' 'Data Lake,' 'Azure Synapse Analytics,' and 'DevOps processes,' ensuring your resume passes automated screening effectively.

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