Akhilesh Mani Tripathi

Software Engineer

Bengaluru, Karnataka, India3 yrs 8 mos experience

Key Highlights

Expert in building scalable data ingestion pipelines.
Reduced compute costs by 60% through Kubernetes migration.
Open-sourced a reusable ETL library for data processing.

Stackforce AI infers this person is a Data Engineering expert in SaaS with a focus on scalable data solutions.

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Skills

Core Skills

Data EngineeringCloud Computing

Other Skills

AirflowApache AirflowApache CamelApache HadoopApache SparkBeamC++Cloud EventsCompetitive ProgrammingContinuous Integration and Continuous Delivery (CI/CD)Data StructuresDelta LakeDjangoEngineeringGoogle Cloud Platform (GCP)

About

🚀 Passionate Data Engineer | Driving Innovation in Data Processing 🚀 🔍 As a dedicated Data Engineer at Zeotap, I specialize in building robust third-party data ingestion pipelines, adeptly handling over 40 billion data processing tasks daily. My expertise lies in crafting scalable solutions that ensure seamless data flow, enabling valuable insights for our clients and stakeholders. 🔧 With a keen eye for optimization and efficiency, I thrive on challenges within the dynamic landscape of data engineering. My commitment to excellence is evident in my ability to design, implement, and maintain cutting-edge systems that drive organizational success. 🔧 My expertise extends to backend technologies like Apache Camel and Play Framework. 💼 Currently seeking new opportunities to further advance my career in data engineering. If you're looking for a driven professional who excels in delivering innovative data solutions, let's connect!

Experience

Inmobi

SDE II

Nov 2024 – Present · 1 yr 4 mos · Bengaluru, Karnataka, India · On-site

Zeotap

2 roles

Software Engineer

Jun 2022 – Oct 2024 · 2 yrs 4 mos

At this role, I worked on making our data platform more reliable, cost-efficient, and scalable. I migrated legacy batch pipelines to Delta Lake with CDC, which made the data more consistent and cut infra costs almost in half. I built a large-scale user profile stitching pipeline that handled over 5 billion user records and helped improve targeting significantly, leading to a big boost in revenue. I also moved all our Spark workloads to Kubernetes, which reduced failures and brought down compute costs by 60%.
To streamline operations, I developed an event-driven orchestration system using Apache Camel and Cloud Events, which helped automate a lot of manual workflows. I tackled Spark data skew issues, saving tens of thousands per month in cloud costs. Along the way, I open-sourced a reusable ETL library called data-io that works across engines like Spark and Beam. I also standardized 40+ partner integrations by moving from custom Scala logic to a SQL-based framework, improving data quality and maintainability. Finally, I migrated over 50 legacy Oozie workflows to Airflow, making them easier to understand and debug.

Delta LakeApache CamelKubernetesApache SparkCloud EventsSQL+3