ShipTech Analytics

Transportation

DataEngineer

₹15–25L ~AI est. Hyderabad, Telangana, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Data Engineer at ShipTech Analytics. Skills: Data engineering, ETL, Data pipelines, AWS. Design scalable NRT streaming data pipelines. Design scalable batch data pipelines”

What You'll Achieve.

Empower operations teams worldwide; Deliver critical insights; Enable faster decision-making; Enable more informed decision-making; Enable operational excellence; Improve customer experience; Deliver automated insights

Industry & Context.

Transportation
Problems you'll solve

Clarifying ambiguities

Eligibility Requirements

Oncall

What They're Looking For.

Must Have

3+ years of data engineering experience, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, Experience with SQL, Experience in at least one modern scripting or programming language, Experience building/operating highly available, distributed systems, Experience with data extraction, Experience with data ingestion, Experience with data processing of large data sets

Nice to Have

Experience with AWS technologies, Experience with non-relational databases, Knowledge of batch data architectures, Knowledge of streaming data architectures

What You'll Do.

Design scalable NRT streaming data pipelines

Design scalable batch data pipelines

Streamline data ingestion

Streamline data processing

Streamline data backfill

Streamline data storage

Streamline data vending

Build operational support modules

Partner with stakeholders

Understand requirements

Implement enhancements for datasets

Collaborate with cross-functional teams

Standardize analytics capabilities

Build AI-powered automation

Leverage AWS cloud technologies

Transform raw data into actionable metrics

Drive continuous improvement

Participate in design discussions

Follow operational best practices

Ensure security compliance

Monitor pipeline health

How You'll Work.

Team & Collaboration

Stakeholders across operations; Analytics teams; Cross-functional teams; Software engineers; TPMs; SDEs; Cross-functional partners; Collaboration across geographies

Full Job Description

Join ShipTech Analytics (STA) as a Data Engineer to build the data and analytics backbone powering Amazon's global transportation network. You'll contribute to our vision of building an intelligent, autonomous, and scalable performance management and decision support system across Amazon Transportation. As a Data Engineer II, you'll work on building standardized data solutions that empower operations teams worldwide. You'll develop both near-real-time (NRT) streaming pipelines and batch processing pipelines that deliver critical insights for decision-making. You'll also build data tools that enable self-service analytics and automate operational tasks, while contributing to innovative AI-powered solutions delivering automated insights across the transportation network. Key job responsibilities - Design and build scalable near-real-time (NRT) streaming and batch data pipelines supporting Amazon's global transportation network. - Build data products and data tools that streamline the complete data lifecycle including data ingestion, processing, backfill, storage, vending, and operational support modules. - Partner closely with stakeholders across operations and analytics teams to understand requirements, design solutions, and deliver datasets and data tools that enable faster, more informed decision-making - Own data quality and implement enhancements for datasets that enable operational excellence and improve customer experience - Collaborate with cross-functional teams to standardize analytics capabilities and build AI-powered automation - Leverage AWS cloud technologies to transform raw data into actionable metrics - Drive continuous improvement through code reviews, design discussions, operational best practices, and security compliance A day in the life You work backwards from what stakeholders need, clarifying ambiguities and building data products and tools. Throughout the day, you're writing code for data pipelines and building tools that handle ingestion, pro

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