Senior Data Engineer

Posted Yesterday
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Dallas, TX, USA
In-Office
Senior level
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Role
Design, build, and operate large-scale batch and real-time data pipelines. Implement ingestion, transformation, orchestration, streaming, and downstream delivery using Kafka, Spark, cloud platforms, and workflow tools. Ensure reliability, scalability, performance, security, secrets management, and observability while collaborating with Agile teams to support enterprise analytics workloads.
Summary Generated by Built In

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Tiger Analytics is looking for an experienced Data Engineer to design, build, and operate large-scale batch and real-time data pipelines that power enterprise data and analytics platforms.

You will work closely with Agile engineering, architecture, and product teams to build reliable, scalable data solutions spanning data ingestion, transformation, orchestration, event streaming, and downstream data delivery. The ideal candidate is someone who enjoys solving complex data engineering problems and building highly available systems that operate at enterprise scale.

Key Responsibilities:

  • Design and develop high-volume batch and real-time data pipelines for enterprise applications and analytics platforms.
  • Build end-to-end data solutions covering ingestion, transformation, orchestration, streaming, and downstream delivery.
  • Develop event-driven and real-time data processing solutions using technologies such as Kafka and Spark.
  • Build scalable data processing solutions using distributed computing frameworks such as Spark, EMR, Hadoop, or equivalent technologies.
  • Develop applications and data solutions using Java, Python, and SQL.
  • Implement and manage workflow orchestration and scheduling for complex data pipelines.
  • Work with cloud data warehouse and cloud-native data platforms to support enterprise-scale workloads.
  • Design solutions with a strong focus on reliability, scalability, performance, security, and low latency.
  • Implement secure approaches for secrets management, credentials, and service-to-service authentication in production environments.

Requirements
  • 4+ years of experience building or operating enterprise-scale data pipelines and orchestration systems.
  • 4+ years of data or application engineering experience with Java, Python, and SQL.
  • 4+ years of experience building and operating real-time or event-driven data systems.
  • 4+ years of experience with distributed data and computing technologies such as Kafka, Spark, EMR, Hadoop, or equivalent.
  • 4+ years of experience working with cloud data warehouse/data platforms at scale.
  • 4+ years of experience with at least one major cloud platform: AWS, Azure, or GCP.
  • 3+ years of experience with workflow orchestration and scheduling tools such as Airflow, Control-M, Autosys, Step Functions, or equivalent.
  • 2+ years of experience implementing secure secrets and credential management in production environments.
  • 2+ years of experience working in Agile engineering teams.
  • Strong understanding of distributed systems, data processing, and enterprise data architecture principles.
  • Familiarity with data observability, including monitoring, alerting, SLA management, pipeline health, and data quality.
  • Strong problem-solving, communication, and collaboration skills.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy,
national origin, ancestry, marital status, protected veteran status, disability
status, or any other basis as protected by federal, state, or local law.

Skills Required

  • 4+ years building or operating enterprise-scale data pipelines and orchestration systems.
  • 4+ years of data or application engineering experience with Java, Python, and SQL.
  • 4+ years building and operating real-time or event-driven data systems.
  • 4+ years experience with distributed data and computing technologies such as Kafka, Spark, EMR, Hadoop, or equivalent.
  • 4+ years working with cloud data warehouse/data platforms at scale.
  • 4+ years experience with at least one major cloud platform: AWS, Azure, or GCP.
  • 3+ years experience with workflow orchestration and scheduling tools such as Airflow, Control-M, Autosys, Step Functions, or equivalent.
  • 2+ years implementing secure secrets and credential management in production environments.
  • 2+ years working in Agile engineering teams.
  • Strong understanding of distributed systems, data processing, and enterprise data architecture principles.
  • Familiarity with data observability: monitoring, alerting, SLA management, pipeline health, and data quality.
  • Strong problem-solving, communication, and collaboration skills.

Tiger Analytics Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tiger Analytics and has not been reviewed or approved by Tiger Analytics.

  • Fair & Transparent Compensation Feedback suggests pay is viewed as fair and market-aligned for many roles and geographies. Consistent, on-time pay and competitive packages in key markets reinforce a generally positive baseline.
  • Healthcare Strength Feedback suggests U.S. medical coverage is strong, with administration via a known benefits platform and plan options seen positively. Health insurance is often regarded as a bright spot within the package.
  • Leave & Time Off Breadth Feedback suggests generous PTO, paid sick days and holidays, and flexible PTO alongside remote-work options. These elements indicate broad time-off provisions available on paper.

Tiger Analytics Insights

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The Company
HQ: Santa Clara, CA
5,000 Employees
Year Founded: 2011

What We Do

Tiger Analytics is a global leader in AI and Analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are Great Place to Work-Certified™ and have been recognized by analyst firms such as Forrester, Gartner, Everest, ISG, HFS, and others. Ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. In India, our offices are located in Chennai, Hyderabad and Bangalore.

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