Principal Engineer - Data Science at LogiNext · Mumbai · 8 - 10 years · ₹21L - ₹30L / yr · Raised funding · Posted 14 Sep 2022
Data Science
Machine Learning (ML)
Python
PHP
JavaLogiNext is looking for a technically savvy and passionate Principle Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.
Responsibilities :
Adapting and enhancing machine learning techniques based on physical intuition about the domain Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, , identify appropriate analytic and statistical methodology, develop predictive models and document process and results Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule and on budget Coordinate and lead efforts to innovate by deriving insights from heterogeneous sets of data generated by our suite of Aerospace products Support and mentor data scientists Maintain and work with our data pipeline that transfers and processes several terabytes of data using Spark, Scala, Python, Apache Kafka, Pig/Hive & Impala Work directly with application teams/partners (internal clients such as Xbox, Skype, Office) to understand their offerings/domain and help them become successful with data so they can run controlled experiments (a/b testing) Understand the data generated by experiments, and producing actionable, trustworthy conclusions from them Apply data analysis, data mining and data processing to present data clearly and develop experiments (ab testing) Work with development team to build tools for data logging and repeatable data tasks tol accelerate and automate data scientist duties
Requirements:
Bachelor’s or Master’s degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field. PhD preferred 8 to 10 years of experience in data mining, data modeling, and reporting 5+ years of experience working with large data sets or do large scale quantitative analysis Expert SQL scripting required Development experience in one of the following: Scala, Java, Python, Perl, PHP, C++ or C# Experience working with Hadoop, Pig/Hive, Spark, MapReduce Ability to drive projects Basic understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo Analysis - Should be able to perform Exploratory Data Analysis and get actionable insights from the data, with impressive visualization. Modeling - Should be familiar with ML concepts and algorithms; understanding of the internals and pros/cons of models is required. Strong algorithmic problem-solving skills Experience manipulating large data sets through statistical software (ex. R, SAS) or other methods Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments Experimentation design or A/B testing experience is preferred. Experience in leading a team required.
Shubham Vishwakarma
Full Stack Developer - Averlon
About LogiNext
About
LogiNext is amongst the fastest growing tech company, providing solutions to simplify and automate the ecosphere of logistics and supply chain management. Our aim is to organize the daunting process of logistics and supply chain planning, with an array of SaaS driven by the most robust enterprise solutions globally.
Our clientele is spread across the globe and we empower them to optimize their supply chain operations by unique data capturing, advanced analytics and visualization. From inception, LogiNext has been an industry leader and recipient of awards like NetApp's Innovative Tech Company of the year, Entrepreneur's Logistics Firm of the Year, Aegis's innovation in Big Data, CIO Choice Award for best supply chain logistics cloud solutions, etc.
Backed by influential industry leaders like PayTM and Indian Angel Network and with partners like IBM, Microsoft, Google, AWS and Samsung, LogiNext has achieved exponential success in a very short span of time and is set to exceed 300% growth by the end of 2016. The true growth hackers, who paved way for this success are the people working exceptionally hard and adding value to our organisation. Our brand ambassadors - that's how we address our people, bring unique values, discipline and problem-solving skills to nurture the innovative and entrepreneurial work culture at LogiNext. Passion, versatility, expertise and a hunger for success is the Mantra chanted by every Logi-Nexter!
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PythonJob Summary
We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.
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- Experience with cloud platforms such as Azure, AWS, or GCP.
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PythonJob Description – Data Engineer
Role: Data Engineer
Experience: 9+ Years
Location: Bangalore / Hyderabad
Notice Period: Immediate to 15 Days
Interview Process: 1st Round – Virtual | 2nd Round – F2F
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Tatvic, is a marketing analytics company focusing on generating insights from data using long association with Google & its infrastructure. We breed,recognize and reward performance. As a company we are growing very fast & we are under transformation. To enable this transformation we need future leaders with eyesight which balances execution & strategic understanding.
Website: www.tatvic.com
2. Role Details
- Role: Lead Data Engineer
- Band: L4
- Department: Data Engineering
- Reporting to: L5 / Head of Delivery
- Location: Ahmedabad
- Job Type: Full Time
- Experience: 6-8 years of relevant experience
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.
3. Mission & Role Overview
- Mission: To create high-level organizational impact by leading a team to design and deliver scalable, high-performance cloud-native data solutions. The Lead Data Engineer (L4) is responsible for ensuring technical excellence—specifically in BigQuery optimization and secure GCP/AWS architectures—while driving the transition to Agentic AI workflows and creating value through the development of L1-L3 engineers.
- Role Overview: This is a pivotal leadership role on the Management Track, responsible for end-to-end data outcomes for the function. The Lead Engineer ensures the quality of engineering execution, manages team utilization and resource allocation, and serves as the primary technical representative in cross-functional forums with Marketing, Strategy, and Product teams.
4. Key Responsibilities
- Lead the design, development, and deployment of scalable and efficient cloud-based data pipelines and architectures.
- Build reusable data solutions and software components that serve multiple customers and use cases.
- Architect cloud environments using GCP, ensuring best practices in IAM, Security, and Networking.
- Conduct Exploratory Data Analysis (EDA) on clickstream and behavioral datasets to derive insights.
- Manage end-to-end ETL processes, including data extraction, transformation, and loading using Python, SQL, and Airflow.
- Design and build production-grade software (APIs, services, internal tools) with sound engineering practices — version control, testing, CI/CD, and code review.
- Extend data platforms with AI capabilities — integrating LLMs, RAG pipelines, and agentic workflows where they add clear business value.
- Perform Root Cause Analysis (RCA) and resolve data quality, pipeline, or application issues.
- Collaborate cross-functionally with Marketing, Insights, Product, and Engineering teams to align data initiatives with business goals.
- Document architectures, design decisions, and operations clearly and consistently.
- Coach and mentor team members, ensuring technical excellence and continuous learning.
- Participate in recruitment and knowledge-sharing through interviews, blogs, and webinars.
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- Strong understanding of clickstream data and data pipeline architecture
- Hands-on experience with cloud platforms (GCP)
- Expertise in SQL, Python, and Airflow
- Solid software engineering foundation — API design, testing, version control, and deployment practices
- Proven ability to perform exploratory data analysis and data validation
- Knowledge of cloud security, IAM, and networking best practices
- Working knowledge of building or integrating AI/LLM-based components into existing systems
- Excellent problem-solving, stakeholder management, and communication skills
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- Certifications such as: Google Cloud Professional Data Engineer / Cloud Architect
- AWS Certified Data Analytics or Azure Data Engineer Associate
- Google Analytics 4 (GAIQ)
- Experience in marketing attribution, commerce data, or analytics ecosystems
- Exposure to cost optimization and cloud resource management
- Experience with agent frameworks (LangChain, ADK, MCP) or LLM APIs
- Experience building automation frameworks or internal data tools
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- Individual Contributor Focus: Operates as the team's best individual contributor instead of building team capability or empowering L3s.
- Information Hoarding: Keeps architectural patterns or tribal knowledge trapped in their head rather than creating reusable playbooks and documentation.
- Avoidance of Conflict: Avoids difficult performance conversations with underperforming team members, allowing capability gaps to persist.
- Activity Over Outcomes: Measures success by "tasks completed" rather than pipeline stability, data accuracy, or business impact.
- Functional Siloing: Fails to build partnerships with Marketing or Product teams, leading to misaligned data delivery.
Our Culture & Perks - Where Passion Meets Purpose:
- Competitive CTC: Based on experience and skillset
- Medical Insurance for you and your family
- Return-to-Work Program for New Moms — because career breaks shouldn’t break momentum
- 1 Work From Home Day/Month — flexibility when life calls
- 2 Birthday Leaves/Year — one for you, one for someone you love
- Monthly Engagement Activities — from game nights to learning sessions
- Inclusive Culture & Equal Opportunity Employer — diversity drives our innovation
- We Think Like Engineers & Athletes: we build, we iterate, we scale, we win — together
- 5-day workweek — because balance drives brilliance
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon