Apache Spark revolutionizes large-scale data processing with its lightning-fast, in-memory distributed computing framework. Designed for complex analytics, machine learning, and streaming workloads, Spark dramatically outperforms traditional MapReduce approaches. Its unified analytics engine supports multiple programming languages (Scala, Python, Java, R) and integrates seamlessly with diverse data sources. Spark's resilient distributed datasets (RDDs) and DataFrame abstractions enable sophisticated data transformations with minimal infrastructure complexity. While powerful, it demands significant computational resources and expertise to optimize. Machine learning libraries (MLlib) and streaming capabilities make it a go-to solution for enterprises processing petabyte-scale datasets across distributed environments.
Role centers on designing, building, and maintaining cloud-based data pipelines for a fast-growing payments environment. You will partner with data analysts, product teams, and business...
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Role centers on designing, building, and maintaining cloud-based data pipelines for a fast-growing payments environment. You will partner with data analysts, product teams, and business stakeholders to ensure high-quality, reliable data drives decisions. The stack is cloud-first, with GCP and BigQuery, plus Hadoop, Spark, and Hive for legacy workloads. You will design ETL pipelines, data models, and integration processes to support reporting and analytics across large, cross-border datasets. The pitch promises scale and reliability, but the description omits governance, security, observability, and real data quality discipline. Core requirements are strong SQL and at least one of Python, Java, or Scala, plus experience with ETL frameworks and data warehousing. It sits at the analytics-engineering seam; whether that is a strength or buzzword fluff depends on how concrete the project scope proves to be in practice.
Data Analyst - Business Intelligence, Regional Logistics
@ shopee
SG | 2025-12-27
Shopee’s BI Data Analyst posting reads like a hybrid: deep analytics plus data engineering chores, spanning from dashboards to building pipelines for logistics across multiple markets. The role...
read more »
Data Analyst - Business Intelligence, Regional Logistics
shopee
(SG) FULL TIME | JOB LISTED
Shopee’s BI Data Analyst posting reads like a hybrid: deep analytics plus data engineering chores, spanning from dashboards to building pipelines for logistics across multiple markets. The role promises cross-functional bite with Data Science/Engineering and Product, consistent with a data platform that must scale. Core tech stack expectations land on SQL and Python, with big-data tools such as Hadoop, Hive SQL, and Spark, plus ETL, Tableau and Looker for visual storytelling. The tension is real: you’re asked to translate qualitative and quantitative signals into actionable plans, while explaining technical concepts to non-tech stakeholders. It’s a decent all-rounder grind in a growing ecommerce operation; the risk is scope creep and ambiguity around success metrics and career ladders. Salary isn’t disclosed, which is a yellow flag in a market that still cares about pay transparency. Opportunities exist for hands-on impact in logistics optimization and cross-market scale.
The Fundamentals of Analytics Engineering gives a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering. It's a book that teaches concepts and best practices, not just tools and technologies.
Data Analyst - Business Intelligence, Marketplace Operations
@ shopee
SG | 2025-12-27
Shopee’s Regional Marketplace BI role asks a hands-on analyst to stitch SQL and Python into dashboards, data pipelines, and playbooks across multiple markets. You’ll chop large datasets, run ETL,...
read more »
Data Analyst - Business Intelligence, Marketplace Operations
shopee
(SG) FULL TIME | JOB LISTED
Shopee’s Regional Marketplace BI role asks a hands-on analyst to stitch SQL and Python into dashboards, data pipelines, and playbooks across multiple markets. You’ll chop large datasets, run ETL, and ship metrics that drive decisions from fraud to operations, while coordinating with product, data science, and regional teams. The tech footprint is solid but not glamorous: Hadoop/Hive, Spark, Tableau or Looker, and room to apply Generative AI for automation and insights. The challenge is real: balancing fast, operational reporting with robust data models, communicating nuanced findings to non‑technical stakeholders, and keeping up with cross‑market governance. Opportunities hinge on influencing policy and process at scale, plus hands-on exposure to AI-enabled analytics. In a crowded BI market, the role stands out if you value practical impact over buzz and prefer breadth to depth.
From the posting, the role is a global marketing analytics-support position that builds reporting and data-extraction solutions with SQL, Python, and Spark, atop a Hadoop ecosystem. It promises...
read more »
From the posting, the role is a global marketing analytics-support position that builds reporting and data-extraction solutions with SQL, Python, and Spark, atop a Hadoop ecosystem. It promises actionable insights to steer campaigns, with collaboration across offices and a data-engineering safety net. The tech stack hints at a legacy‑leaning big data setup rather than a cloud-native analytics dream, and the emphasis on reporting work suggests heavy ETL and dashboard duties more than true engineering or data science. Expect to wrangle messy marketing data, manage evolving tracking needs, and juggle cross‑team priorities in a fast-paced environment. The absence of salary details and a clear ownership model makes the opportunity feel promising in title but murky in scale and career progression.
Junior Data Analyst - Business Intelligence, Regional Operations
@ shopee
SG | 2025-12-26
Shopee's Regional Operations role promises hands-on BI work across big data, building dashboards and pipelines to measure day-to-day efficiency and strategic impact. The job requires SQL and...
read more »
Junior Data Analyst - Business Intelligence, Regional Operations
shopee
(SG) FULL TIME | JOB LISTED
Shopee's Regional Operations role promises hands-on BI work across big data, building dashboards and pipelines to measure day-to-day efficiency and strategic impact. The job requires SQL and Python, plus familiarity with Hadoop, Hive, Spark, ETL tools, and visualization platforms like Tableau or Looker. It asks for 0-3 years and a business analytics or STEM degree, which is typical, but the real work is data infrastructure alongside reporting, converting qualitative and quantitative inputs into scalable playbooks. The environment is cross-market and cross-functional, so stakeholder management and translating tech concepts into actionable plans matter as much as modelling. The risks include a heavy emphasis on data engineering tasks under a BI banner, potential tooling churn, and the need to navigate regional data governance. Opportunities lie in end-to-end ownership of metrics and practical impact on operations, not just dashboards.
This position at Deloitte's Artificial Intelligence & Data team in Singapore is ideal for fresh graduates or recent entrants looking to build a technical foundation in data engineering amidst an...
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This position at Deloitte's Artificial Intelligence & Data team in Singapore is ideal for fresh graduates or recent entrants looking to build a technical foundation in data engineering amidst an avalanche of corporate flummery. Candidates will wield SQL, Oracle, and an assortment of Big Data tools while navigating data integration complexities. The promise of working with industry giants might be enticing, but the reality of rampant buzzword usage—'cognitive technologies'—raises eyebrows. With a focus on emerging technologies, the role offers genuine opportunities for growth and learning, assuming you can survive the inevitable bureaucratic layers. The requirement for knowledge in AI, ML, and various development methodologies indicates a demanding expectations set, which, combined with a sprinkle of empty panegyrics, might leave you levelling up your coffee consumption just to stay afloat.
The BigQuery Cost Optimization Guide is a valuable resource that offers a deep dive into understanding and managing the complexities of BigQuery costs. It provides practical guidelines and strategies to help you optimize both storage and compute expenses, ensuring you get the most value out of...
The role requires supporting marketing functions with data and insight, using SQL, Python, and Spark, while working with big data in the Hadoop ecosystem. The job emphasizes problem-solving,...
read more »
The role requires supporting marketing functions with data and insight, using SQL, Python, and Spark, while working with big data in the Hadoop ecosystem. The job emphasizes problem-solving, attention to detail, and collaboration with cross-functional teams. While the skills align with data engineering, the focus on marketing analytics and the inclusion of VBA/Spark add a unique dimension. The role stands out for its practical focus on real-world data challenges, though the emphasis on marketing may limit its appeal to purely data engineering audiences. The salary is not explicitly provided, and the tools list is sparse but includes relevant technologies.
This role presents a challenge for a data engineer seeking to deliver meaningful value in a fast-paced, multi-platform environment. The position requires deep technical proficiency in SQL, Python,...
read more »
This role presents a challenge for a data engineer seeking to deliver meaningful value in a fast-paced, multi-platform environment. The position requires deep technical proficiency in SQL, Python, and big data technologies, with a focus on ETL pipeline design and maintenance. While the job description highlights strong analytical and communication skills, it lacks specific details about the company’s culture, team dynamics, or the extent of responsibility in a real-world setting. The role is technically demanding but lacks clarity on the company’s approach to innovation and collaboration. The opportunity lies in working with a large, dynamic organization that values technical excellence, but the description does not fully convey the nuances of the environment or the potential for growth within the team.
Role centers on designing, building, and maintaining cloud-based data pipelines for a fast-growing payments environment. You will partner with data analysts, product teams, and business stakeholders to ensure high-quality, reliable data drives decisions. The stack is cloud-first, with GCP and BigQuery, plus Hadoop, Spark, and Hive for legacy workloads. You will design ETL pipelines, data models, and integration processes to support reporting and analytics across large, cross-border datasets. The pitch promises scale and reliability, but the description omits governance, security, observability, and real data quality discipline. Core requirements are strong SQL and at least one of Python, Java, or Scala, plus experience with ETL frameworks and data warehousing. It sits at the analytics-engineering seam; whether that is a strength or buzzword fluff depends on how concrete the project scope proves to be in practice.
Data Analyst - Business Intelligence, Regional Logistics
shopee
(SG) FULL TIME | JOB LISTED
Shopee’s BI Data Analyst posting reads like a hybrid: deep analytics plus data engineering chores, spanning from dashboards to building pipelines for logistics across multiple markets. The role promises cross-functional bite with Data Science/Engineering and Product, consistent with a data platform that must scale. Core tech stack expectations land on SQL and Python, with big-data tools such as Hadoop, Hive SQL, and Spark, plus ETL, Tableau and Looker for visual storytelling. The tension is real: you’re asked to translate qualitative and quantitative signals into actionable plans, while explaining technical concepts to non-tech stakeholders. It’s a decent all-rounder grind in a growing ecommerce operation; the risk is scope creep and ambiguity around success metrics and career ladders. Salary isn’t disclosed, which is a yellow flag in a market that still cares about pay transparency. Opportunities exist for hands-on impact in logistics optimization and cross-market scale.
Data Analyst - Business Intelligence, Marketplace Operations
shopee
(SG) FULL TIME | JOB LISTED
Shopee’s Regional Marketplace BI role asks a hands-on analyst to stitch SQL and Python into dashboards, data pipelines, and playbooks across multiple markets. You’ll chop large datasets, run ETL, and ship metrics that drive decisions from fraud to operations, while coordinating with product, data science, and regional teams. The tech footprint is solid but not glamorous: Hadoop/Hive, Spark, Tableau or Looker, and room to apply Generative AI for automation and insights. The challenge is real: balancing fast, operational reporting with robust data models, communicating nuanced findings to non‑technical stakeholders, and keeping up with cross‑market governance. Opportunities hinge on influencing policy and process at scale, plus hands-on exposure to AI-enabled analytics. In a crowded BI market, the role stands out if you value practical impact over buzz and prefer breadth to depth.
From the posting, the role is a global marketing analytics-support position that builds reporting and data-extraction solutions with SQL, Python, and Spark, atop a Hadoop ecosystem. It promises actionable insights to steer campaigns, with collaboration across offices and a data-engineering safety net. The tech stack hints at a legacy‑leaning big data setup rather than a cloud-native analytics dream, and the emphasis on reporting work suggests heavy ETL and dashboard duties more than true engineering or data science. Expect to wrangle messy marketing data, manage evolving tracking needs, and juggle cross‑team priorities in a fast-paced environment. The absence of salary details and a clear ownership model makes the opportunity feel promising in title but murky in scale and career progression.
Junior Data Analyst - Business Intelligence, Regional Operations
shopee
(SG) FULL TIME | JOB LISTED
Shopee's Regional Operations role promises hands-on BI work across big data, building dashboards and pipelines to measure day-to-day efficiency and strategic impact. The job requires SQL and Python, plus familiarity with Hadoop, Hive, Spark, ETL tools, and visualization platforms like Tableau or Looker. It asks for 0-3 years and a business analytics or STEM degree, which is typical, but the real work is data infrastructure alongside reporting, converting qualitative and quantitative inputs into scalable playbooks. The environment is cross-market and cross-functional, so stakeholder management and translating tech concepts into actionable plans matter as much as modelling. The risks include a heavy emphasis on data engineering tasks under a BI banner, potential tooling churn, and the need to navigate regional data governance. Opportunities lie in end-to-end ownership of metrics and practical impact on operations, not just dashboards.
This position at Deloitte's Artificial Intelligence & Data team in Singapore is ideal for fresh graduates or recent entrants looking to build a technical foundation in data engineering amidst an avalanche of corporate flummery. Candidates will wield SQL, Oracle, and an assortment of Big Data tools while navigating data integration complexities. The promise of working with industry giants might be enticing, but the reality of rampant buzzword usage—'cognitive technologies'—raises eyebrows. With a focus on emerging technologies, the role offers genuine opportunities for growth and learning, assuming you can survive the inevitable bureaucratic layers. The requirement for knowledge in AI, ML, and various development methodologies indicates a demanding expectations set, which, combined with a sprinkle of empty panegyrics, might leave you levelling up your coffee consumption just to stay afloat.
The role requires supporting marketing functions with data and insight, using SQL, Python, and Spark, while working with big data in the Hadoop ecosystem. The job emphasizes problem-solving, attention to detail, and collaboration with cross-functional teams. While the skills align with data engineering, the focus on marketing analytics and the inclusion of VBA/Spark add a unique dimension. The role stands out for its practical focus on real-world data challenges, though the emphasis on marketing may limit its appeal to purely data engineering audiences. The salary is not explicitly provided, and the tools list is sparse but includes relevant technologies.
This role presents a challenge for a data engineer seeking to deliver meaningful value in a fast-paced, multi-platform environment. The position requires deep technical proficiency in SQL, Python, and big data technologies, with a focus on ETL pipeline design and maintenance. While the job description highlights strong analytical and communication skills, it lacks specific details about the company’s culture, team dynamics, or the extent of responsibility in a real-world setting. The role is technically demanding but lacks clarity on the company’s approach to innovation and collaboration. The opportunity lies in working with a large, dynamic organization that values technical excellence, but the description does not fully convey the nuances of the environment or the potential for growth within the team.
